MOLECULAR ANALYSIS OF SMALL RNA AND SMALL PROTEIN REGULATION OF ESCHERICHIA COLI STRESS RESPONSES
BY
CHELSEA R. LLOYD
DISSERTATION
Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Microbiology in the Graduate College of the University of Illinois at Urbana-Champaign, 2018
Urbana, Illinois
Doctoral Committee:
Associate Professor Carin K. Vanderpool, Chair Professor John E. Cronan Professor William W. Metcalf Professor Peter A. B. Orlean
Abstract
Small RNA (sRNA) regulators control gene expression throughout all domains of life. In bacteria, they typically affect virulence, metabolism, and stress response genes posttranscriptionally through imperfect antisense pairing with their mRNAs. While most sRNAs are non-coding, a small number act as mRNAs themselves by encoding functional proteins. This study examines the regulatory and physiological effects of both a non-coding sRNA, DicF, and the protein product of a dual-function sRNA, SgrS in
Eschericha coli.
The sRNA SgrS encodes the small 43-amino acid protein SgrT. Both molecules are expressed during glucose-phosphate stress - a bacteriostatic condition in which phosphosugars accumulate in the cell either because of mutations in glycolysis or because of the transport of non-metabolizable glucose analogs such as αMG or 2DG. While both
SgrT and SgrS base pairing can independently mitigate glucose-phosphate stress, they do so through distinct mechanisms. SgrS base pairing destabilizes the mRNA of the respective major and minor glucose transporters PtsG and ManXYZ, thereby inhibiting synthesis of additional glucose permeases and restricting further influx of non- metabolizable sugars. In this study we demonstrate that SgrT acts to specifically inhibit the transport activity of preexisting PtsG transporters, but does not affect ManXYZ. We reveal that by targeting PtsG transport activity SgrT not only prevents influx of non- metabolizable αMG, but also overrides inducer exclusion allowing alternative carbon sources to be transported and metabolized during stress. We also uncover the regions of
PtsG that are required for SgrT regulation.
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Although the precise nature of glucose-phosphate stress is not well understood, this work establishes that sugar phosphates are not inherently toxic, but most likely inhibit growth by depleting glycolytic intermediates, as these are expended to transport sugars and not are replenished due to a blockage in glycolysis. Sugar phosphate accumulation is, however, problematic and cells cope by effluxing excess sugars out of the cell. Phosphosugar efflux must be preceded by dephosphorylation and previous studies found that the phosphatase YigL is posttranscriptionally stabilized by SgrS under stress to promote this process. However, we still have yet to identify the efflux pump through which these sugars are flushed out of the cell. Here we provide evidence that the multidrug efflux channel TolC may be involved as tolC mutants exhibit impaired αMG efflux and more impaired growth when combined with an sgrS mutation.
While the benefits of SgrS and SgrT to E. coli physiology are clear, the role of the sRNA DicF remains elusive. DicF is produced from the cryptic prophage Qin and while we have yet to identify the conditions under which it is naturally produced, ectopic expression of DicF leads to growth inhibition and filamentation. Previous work has identified a few DicF targets including ftsZ, which causes filamentation, no single target can be attributed to the growth defect we observe. Here we use a combination of approaches to uncover the novel targets ahpC and mdfA. While mutating ahpC has no effect on growth, mdfA (which encodes a proton/sodium/potassium antiporter) mutants partially rescue cell growth. Additionally, under alkaline conditions mdfA mutants expressing DicF are able to outcompete wild type cells. While there are more targets to uncover that contribute to growth inhibition and we have more to learn about DicF regulation and why its maintenance is beneficial, this study provides new insights into E.
iii coli physiology during DicF expression and highlights the challenges associated with characterizing sRNA targetomes.
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Acknowledgements
First and foremost I want to thank Dr. Cari Vanderpool for being such an inspiring and supportive advisor. She gave me the freedom and opportunity to pursue my passions of teaching and mentorship, and to answer my own scientific questions. She also fostered a fun, energized, and collaborative work environment that made lab feel like a second (or first) home. I also want to acknowledge the past and present members of the
Vanderpool lab for being amazing coworkers, friends, travel buddies, Curie sitters, and
Secret Santas.
I would like to thank my past and present committee members: Dr. John Cronan,
Dr. Bill Metcalf, Dr. Peter Orlean, Dr. Jeff Gardner, and the late Dr. Charles Miller for all of their invaluable guidance and advice. Additionally, I would also like to thank Dr. Jim
Slauch for his helpful feedback during our group meetings. For their roles in developing and supporting my teaching interests and abilities, I would like to thank Brad Mehrtens,
Melissa Reedy, and J.P. Swigart. I am also extremely grateful for Deb LeBaugh, Diane
Tsevelekos, and Shawna Smith for all of their help behind the scenes and for letting me nerd-out about fecal bacteria in the microbiology office. I could not have asked for a better, more collaborative department to be a part of.
In addition to wonderful research and teaching support I have received at UIUC, I also want to acknowledge the members of Illini Pole Fitness, Carnivale Debauche, and the Defy Gravity community for providing a creative outlet and supportive space for my mind and body. I have made so many personal gains because of those amazing humans.
I have been privileged to have a host of teachers and mentors that developed and encouraged my interest in studying science. Thanks to my undergraduate research
v advisors at the University of Iowa, Dr. Rich Roller and Dr. John Kirby, for the opportunity to fall in love with research in their labs and for encouraging me to attend graduate school at UIUC. Thanks to my Quincy Senior High School teachers Sarah
Stewart, Jackie Stewart, and Dr. Sandra Spalt-Fulte for being inspirational instructors and for encouraging me to pursue a career in STEM; and thanks to Kathi Dooley for shaping me into the person I am today through performance and Dooleycising. I am especially thankful to my 4th grade science teacher Marilyn Meyer for sparking my lifelong love for microbiology by reading graphic excerpts from “The Hot Zone” by Richard Preston to our class. That was a transformative moment when I realized just how powerful microbes could be.
Last but not least, I want to thank my family for being so encouraging and supportive during my PhD. Thanks to my Aunt Marilyn, without whom I would not have been able to attend college. Thanks to my late father Ron for his encouragement, curiosity, and for igniting my interest in science. Thanks to my mom Sharon who has always been my biggest cheerleader – who has always been excited about my work and given me unwavering support. She always told me, “Science is like Italian – I love hearing it, but I don’t understand a word of it.” I love her bigger than the universe.
Lastly, I thank my amazing partner Jake and cat Curie for their compassion, encouragement, and support through the highs and lows, but mostly I thank them for pretending to be as excited as I am about bacterial physiology.
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This work is dedicated to my family.
I love you bigger than the universe.
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Table of Contents
Chapter 1: Introduction...... 1 1.1 Escherichia coli as a model organism ...... 1 1.2 Small RNA (sRNA) regulators ...... 2 1.2.1 Regulatory sRNAs in eukaryotes and archaea...... 2 1.2.2 Regulatory sRNAs in bacteria ...... 4 1.2.3 Dual-function sRNAs...... 7 1.3 The carbohydrate phosphoenolpyruvate phosphotransferase system (PTS) ...... 8 1.3.1 The major glucose transporter EIIBCGlc (PtsG)...... 10 1.3.2 The broad substrate transporter EIIABCDMan (ManXYZ) ...... 11 1.3.3 The N-acetylglucosamine transporter EIIBCANag (NagE)...... 12 1.4 Glucose-phosphate stress...... 13 1.4.1 Induction of the stress response by the transcription factor SgrR ...... 17 1.4.2 The small RNA SgrS ...... 18 1.4.3 The small protein SgrT ...... 20 1.5 The small RNA DicF ...... 22 1.5.1 Targets of DicF regulation...... 23 1.5.2 Effects of DicF on E. coli physiology...... 24 1.6 Aim of the study...... 25 1.7 Figures...... 27
Chapter 2: Materials and methods ...... 28 2.1 Strains and plasmid construction ...... 28 2.2 β-galactosidase assays...... 30 2.3 [14C]αMG transport and efflux assays ...... 31 2.4 Immunostaining and superresolved single-fluorophore microscopic imaging...... 33 2.5 Growth assays ...... 34 2.6 Whole-genome sequencing and data analyses...... 35 2.7 Microscopy ...... 36 2.8 Pulse-chase assay...... 36 2.9 Tables...... 37
Chapter 3: The small protein SgrT controls transport activity of the glucose- specific phosphotransferase system ...... 42 3.1 Introduction...... 42 3.2 Results...... 44 3.2.1 Ectopic production of SgrT inhibits cell growth on minimal glucose medium ...... 44 3.2.2 SgrT inhibits PtsG but not ManXYZ...... 45 3.2.3 SgrT localizes to the membrane in a PtsG-dependent manner ...... 46 3.2.4 The EIIC domain of PtsG is required for full sensitivity to SgrT...... 47 3.2.5 PtsG(V12F) but not PtsG(P384R) is resistant to SgrT-mediated transport inhibition...... 49 3.2.6 SgrT strongly inhibits preexisting PtsG transporters...... 51
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3.2.7 SgrT-mediated inhibition of PtsG prevents inducer exclusion, promoting growth by allowing utilization of alternative carbon sources ...... 52 3.3 Discussion...... 53 3.4 Figures...... 58
Chapter 4: The impact of glucose-6-phosphate and tolC mutants on glucose- phosphate stress ...... 66 4.1 Introduction...... 66 4.2 Results...... 68 4.2.1 Glucose-6-phosphate rescues glucose-phosphate stress but does not affect cellular αMG transport...... 68 4.2.2 Mutating the multidrug efflux pump tolC in an sgrS background further diminishes cell growth under glucose-phosphate stress ...... 69 4.2.3 tolC mutants experience higher induction of the glucose-phosphate stress response...... 70 4.2.4 tolC mutants exhibit impaired αMG efflux...... 71 4.3 Discussion...... 71 4.4 Figures...... 74
Chapter 5: Posttranscriptional regulation of the multidrug efflux pump MdfA by DicF contributes to growth inhibition and filamentation in E. coli ...... 79 5.1 Introduction...... 79 5.2 Results...... 80 5.2.1 Prediction and validation of novel DicF targets using combined approaches...... 80 5.2.2 DicF posttranscriptionally represses ahpC ...... 84 5.2.3 mdfA mutants partially suppress DicF-mediated growth inhibition and filamentation ...... 85 5.2.4 DicF posttranscriptionally upregulates mdfA mRNA ...... 86 5.2.5 mdfA mutants ectopically expressing DicF exhibit a growth advantage at alkaline pH ...... 87 5.3 Discussion...... 88 5.4 Figures...... 91
Chapter 6: Conclusions and future directions...... 103
References...... 109
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Chapter 1: Introduction1
1.1 Escherichia coli as a model organism
First discovered in 1884, Bacterium coli commune was isolated by the German microbiologist and pediatrician Theodor Escherich from the stool of a breastfed infant
[43]. It was later renamed Escherichia coli after its discoverer. In his work, Escherich described the bacteria as having “a massive luxurious deep growth” stating “culturing them on gelatin plates is easily achieved.” This cultivability has allowed E. coli to grow into the valuable and versatile model organism we still use today. In addition to being fast growing and resilient, it is highly genetically tractable, allowing it to be studied in great detail and used as a tool to answer complex questions in molecular biology, physiology, genetics, genetic engineering, and evolution. A few notable examples are the use of E. coli in elucidating the genetic code [29], mechanisms of gene regulation [76], and DNA replication [104]. After the discovery of restriction enzymes [109, 118], E. coli could be manipulated for genetic recombineering and was used to synthesize human insulin [77] and human growth hormone [32] among other therapeutic proteins [84].
Again, because of its short generation time and ability to amass large population volumes, E. coli was used to study rare events, like mutations [102, 112], and is still used in long-term evolution experiments to study the effects of mutations on genetic adaptation [13].
While there are numerous wild and domestic strains of E. coli in use, the most popular laboratory strain is E. coli K-12, namely the MG1655 derivative. The K-12 strain was isolated from the stool of a diphtheria patient in 1922 and the MG1655
1 Chapter contains material from the following publication: Vanderpool C.K., Balasubramanian D., Lloyd C.R., Biochimie, 2011.
1 derivative was developed by curing it of its lambda phage via ultraviolet light treatment, and its F plasmid with acridine orange treatment [7]. E. coli K-12 MG1655 has been used as a standard representative laboratory strain since it endured the least genetic manipulation of its K-12 brethren; for this reason it was the first E. coli strain to be completely sequenced in 1997 [14].
1.2 Small RNA (sRNA) regulators
After the inception of the central dogma of molecular biology [28], RNA was regarded as an adaptor molecule - an intermediate between DNA and protein. This was experimentally verified by the discovery and characterization of tRNA [67] and mRNA
[21]. Following these discoveries, however, more RNA species began to be identified and characterized beginning with non-coding eukaryotic small nuclear RNAs (snRNAs) – which were later shown to not only be involved in mRNA splicing, but to possess catalytic or ribozyme activity [49]. From there, non-coding RNA elements have been discovered in all three domains of life performing diverse biological functions via diverse mechanisms.
1.2.1 Regulatory sRNAs in eukaryotes and archaea
Eukaryotes employ three major types of small RNAs to perform regulatory functions in the cell: micro RNAs (miRNAs), small interfering RNAs (siRNAs), and
PIWI-associated small RNAs (piRNAs). miRNAs were first discovered in 1993 and typically regulate mRNA translation by base pairing to the transcript 3’ UTR and inhibiting translation, sometimes enhancing degradation. These are typically endogenously produced small RNA species ~20-30 nucleotides in length [103, 124], although recent work has revealed they are highly enriched in many human body fluids
2 and can be transmitted from mothers to infants via breastmilk to influence cellular and immune system development [2]. In contrast, siRNAs are exogenously produced from invasive dsRNA species into similarly sized products. Both miRNAs and siRNAs use
RNA Induced Silencing Complexes (RISCs) to process them from their precursors using
Dicer RNAses, and use RNA-scaffolding Argonaute (Ago) proteins to facilitate target silencing [24]. Similar to Argonaute, PIWI is a small RNA associative protein; therefore
RNAs that bind this protein are known as PIWI-associated RNAs (piRNAs). These
RNAs are slightly larger than other eukaryotic small RNAs at 26-31 nucleotides in length and base pair with transposon mRNAs; this is important in germ cell development, particularly spermatogenesis [87, 124].
Archaeal sRNAs share similarities with both eukaryotic and bacterial small RNA species. Like eukaryotic sRNAs they can often target mRNA 3’ UTRs; however, like bacteria, they are longer (ranging from ~50 to 500 nucleotides), can also target 5’ UTRs, and can have cis-acting, trans-acting, and dual-function (protein coding) capabilities.
These sRNAs have been shown to regulate adaptation to environmental conditions, stress, development, and behavior. Many of these functions were elucidated using deletion mutant analysis. Similar to eukaryotic miRNA deficiencies, deletion of archaeal sRNAs can result in severe phenotypes, whereas bacterial sRNA deletion very rarely exhibits phenotypes [6].
While archaeal sRNAs seem to carry out regulation by base pairing mRNA ribosome binding sites, it is unclear how prevalent accessory proteins are in facilitating this interaction. Most bacterial sRNAs depend on the RNA chaperone Hfq for stability and target pairing, and Eukaryotes make use of homologous Sm scaffolding proteins to
3 form RNA complexes. It is unclear how archaea make use of the Hfq homolog Lsm or
Sm-like archaeal proteins (SmAPs) in riboregulation – whether they act as scaffolding or chaperone proteins (or both) remains to be determined [6, 126].
1.2.2 Regulatory sRNAs in bacteria
Small RNA species were found in bacteria as early as 1967 when the 6S RNA was detected by RNA fractionation [66]. The function of this sRNA, however, was not elucidated until 2000 when it was found to regulate σ70-RNA polymerase activity [180] by mimicking the structure of an open promoter complex [12]. While fractionation permitted detection of sRNAs, the first indication that they performed regulatory roles was in 1981 with the discovery of the 108-nucleotide-long RNA I from the ColE1 plasmid. It was discovered when N-methyl-N’-nitro-N-nitrosoguanidine mutagenesis permitted the ColE1 plasmid to co-reside with a previously incompatible plasmid. This permissive mutation was within the RNA I gene. RNA I was found to hybridize to and negatively regulate the DNA replication primer thereby inhibiting plasmid replication, causing incompatibility [168, 169]. Three years later, the first chromosomally encoded canonical sRNA MicF was discovered and characterized. This gene was serendipitously found to repress translation of the OmpF protein when it was cloned and overexpressed from a plasmid. The 174-nucleotide-long MicF RNA was found to hybridize with the ompF mRNA at the ribosome binding site thereby posttranscriptionally inhibiting its translation [121].
While bacterial sRNAs can affect transcription [12] and translation [37] directly, they most often perform regulation at the posttranscriptional level and can be broadly classified into two categories: cis- and trans- acting sRNAs. Cis or antisense sRNAs are
4 encoded antisense to their target and therefore have perfect complementarity to the mRNA. These sRNAs most often repress translation by occluding the ribosome binding site [31], but can also enhance translation by stabilizing the message, such as GadY stabilization of the 3’ UTR of the gadX message under acid stress [131]. Trans-encoded sRNAs are the most abundant class in bacteria. As the name suggests, these are encoded in trans to their target mRNAs and therefore have imperfect base complementarity, often relying upon RNA chaperones such as Hfq, CsrA, or ProQ to stabilize the base pairing interaction [3]. Hfq binds AU-rich single stranded regions of both sRNAs and mRNA targets [156]. In the absence of Hfq, many sRNAs are unstable and unable to regulate their targets in vivo [58, 190]. In vitro, Hfq has been shown to increase the rate of sRNA- mRNA binding [85, 155] and to remodel RNA secondary structures [54, 122].
Trans-encoded sRNAs range in size from ~50 to 500 nucleotides in length and act by various mechanisms. They can negatively impact translation initiation by preventing ribosomal access to transcripts or positively influence translation by remodeling inhibitory secondary structures that mask the RBS. They can also positively or negatively affect mRNA stability by revealing or occluding RNase E cleavage sites [15].
The canonical regulatory mechanism involves Hfq-mediated sRNA pairing near the mRNA Shine-Dalgarno sequence, preventing ribosome binding [158]. This RNA duplex can then be targeted for degradation by the endoribonuclease RNase E and the degradosome complex, which consists of RNA helicase RhlB, the 3’ exoribonuclease
PNPase, and the glycolytic enzyme enolase [57]. Although many sRNAs perform canonical regulation, due to imperfect base pairing, a single sRNA can have an extensive
5 targetome with which it can evoke many of the aforementioned mechanisms; such is the case with SgrS, which will be described later in detail [16].
Directed identification of trans-encoded sRNAs was not without its challenges.
Non-coding sRNAs cannot be identified by searching for open reading frames; and because of their small size, expression under specific stress conditions, modest regulatory effects, and imperfect pairing, are missed by transposon inactivation and other mutagenic screens. Early computational tools to identify sRNAs searched for orphan promoters,
Rho-independent terminators, and conserved secondary structures within intergenic regions. Experimental tools were later developed to discover sRNAs and their targets including microarray analysis of transcripts from intergenic regions, and RNA co- immunoprecipitation with Hfq [110]. Although modern RNA-seq based methods have replaced microarrays to study transcriptomes, today we still heavily rely upon ever- evolving computational tools and Hfq-based immunoprecipitation techniques to identify new sRNAs and their targets [146].
sRNA target identification is also challenging and relies on similar techniques as sRNA identification. Because sRNA-mRNA interactions are based on short and imperfect base pairing, computational predictions can yield many false positive interactions. Conversely, novel, non-canonical regulatory mechanisms are frequently being characterized, which means noncanonical sRNA binding sites - such as those within the mRNA coding region - may be excluded in cursory computational searches
[132]. While RNA-seq is still used to evaluate transcriptomic changes upon ectopic sRNA expression, new protein based RNA pulldowns are being used to identify direct sRNA binding partners. These include the Hfq-based MS2 affinity purification coupled
6 with RNA sequencing (MAPS) [100] and RNA interaction by ligation and sequencing
(RIL-seq) [117]; the RNase E-based UV-crosslinking, ligation and sequencing of hybrids
(CLASH) [181]; and gradient profiling by sequencing (Grad-seq), which led to the discovery of a new class of ProQ binding sRNAs [160]. Despite advances in these sRNA targetome discovery techniques, experimentally verifying these interactions is still a labor-intensive process often using translational reporter fusions to measure posttranscriptional regulation, as well as mutational analysis and RNA footprinting to confirm base pairing sites.
1.2.3 Dual-function sRNAs
Most trans-acting sRNAs are non-coding, however there are a few notable examples that also harbor small ORFs; these are referred to as dual-function sRNAs. To date only five protein-coding sRNAs and their proteins have been well characterized [55,
172]. The relationships between dual-function sRNAs and their associated proteins are quite variable. Of these five dual-function sRNAs, SgrS and SgrT are the only sRNA- protein duo where the riboregulation and protein functions act independently in the same physiological pathway. Though the SgrS base pairing region and open reading frame are only 15 nucleotides apart, work from our lab has shown that these functions are temporally distinct, as SgrS riboregulation occurs early in the stress response and impedes SgrT translation - most likely through Hfq competition with ribosome binding, but possibly because of sRNA-mRNA co-degradation [11]. Other sRNA-protein duos are completely mutually exclusive due to extensive overlap between the base pairing region and ORF; this is the case with RNA III and SR1. RNA III from S. aureus riboregulates several mRNAs including the positive target hla, which encodes α-
7 hemolysin. RNA III encodes δ-hemolysin, which is itself riboregulated; the 5’ and 3’ regions RNAIII are involved in intramolecular interactions such that the RBS of hld is occluded in a secondary structure [9]. The SR1 base pairing region of Bacillus subtilis also overlaps the ORF encoding SR1P. SR1 regulates ahp, encoding a regulator of the arginine catabolic operons, while SR1P binds the GapA protein and also stabilizes the gapA transcript. Six out of the seven regions of complementarity between SR1 and ahrC mRNA are located within the SR1P coding region. The outlying complementary region, located within the SR1 terminator stem-loop, is required for the initial contact between
SR1 and the ahrC mRNA, whereas the other regions contribute to pairing efficiency [56,
63]. This arrangement might be important to ensure that SR1 is used to its maximal potential as an RNA molecule by allowing the region of SR1 most critical for pairing initiation to be physically separated from the peptide-coding region [172].
How these dual-function molecules evolved is an interesting question; which came first the proverbial chicken or the egg? With SgrS, the base pairing region is more highly conserved than the open reading frame [71], yet the SgrT protein has a narrower target specificity [111]. Conversely, with the Pseudomonas aeruginosa sRNA PhrS, the peptide is more conserved [162]. Perhaps it is advantageous to make the most of genetic material by evolving multiple uses for a single RNA. Or, perhaps under stress conditions, when sRNAs are more likely to be expressed, producing a protein is too energetically costly and this function was dispensed with.
1.3 The carbohydrate phosphoenolpyruvate phosphotransferase system (PTS)
Bacteria must be able to sense, transport, and regulate the metabolism of a variety of carbon sources in response to changing environmental conditions. This is primarily
8 achieved via the phosphoenolpyruvate phosphotransferase system (PTS) in which the glycolytic intermediate phosphoenolpyruvate (PEP) is used as a high energy phosphate donor to facilitate group translocation - the coupling of transport and phosphorylation - of a cognate sugar substrate. This reaction yields one molecule of phosphorylated sugar primed for metabolism, as well as one molecule of pyruvate. Compared to PTS- independent sugar transport, where more than one ATP equivalent is expended both for transport and phosphorylation, the PTS is relatively more energy efficient, particularly for facultative anaerobes like E. coli where ATP must be conserved under anaerobic conditions [145].
Phosphate transfer is achieved through several proteins acting in a phosphorelay cascade; the phosphoryl group hydrolyzed from PEP is initially transferred to enzyme I
(EI – encoded by ptsI), then to histidine protein (HPr – encoded by ptsH) – both of which are soluble and sugar nonspecific proteins. From there, the phosphoryl group is transferred to a soluble enzyme II domain and lastly to a membrane-bound EII, which carries out vectorial transport. These EIIs are sugar specific (there are upwards of 20 in
E. coli) and have various structural domains - EIIA, EIIB, EIIC, (and sometimes EIID) - as well as various configurations: some EII domains are completely fused by linkers into a large single protein, as with the E. coli mannitol PTS (EIICBAMtl). Some domains remain completely independent, as with the cellobiose PTS (EIICCel, EIIBCel, and EIIACel); and others may be fused in other variable arrangements as with glucose (EIICBGlc and
EIIAGlc) and mannose (EIICDMan and EIIABMan) [145, 166].
9 In addition to facilitating sugar transport, the PTS – particularly the glucose PTS – is involved in chemotaxis toward increasing sugar concentrations [128], and regulation of sugar utilization via carbon catabolite repression [59, 70, 74, 89].
1.3.1 The major glucose transporter EIIBCGlc (PtsG)
The glucose enzyme II complex consists of two sugar-specific subunits: The permease PtsG - also known as EIICBGlc (encoded by ptsG), and EIIAGlc (encoded by crr). Each subunit is expressed from a different transcript and functions cooperatively as well as independently. PtsG is responsible for coupling glucose translocation with its phosphorylation and is composed of two domains fused by a highly conserved linker: a membrane-bound domain, EIIC, that dictates substrate specificity [144], and a soluble domain, EIIB. EIIAGlc not only activates the glucose transporter (PtsG) via phosphorelay, but also activates the trehalose transporter TreB [91] and the N-acetylmuramic acid transporter MurP [30]. In addition to its role in phosphotransfer, EIIAGlc is also involved in regulating carbon utilization in the cell, instigating both carbon catabolite repression and inducer exclusion [70, 89]. When glucose is actively transported, EIIAGlc is engaged in phosphotransfer resulting in a net dephosphorylated state; under these circumstances dephosphorylated EIIAGlc binds MalK, LacY, GlpK, and MerB thereby blocking import of carbon sources less favorable to glucose. Conversely, when glucose is absent, EIIAGlc remains phosphorylated; in this state P~EIIAGlc activates adenylate cyclase, which increases intracellular cAMP levels and activates the transcription factors Mlc and
CRP:cAMP, which then control sugar utilization genes [34].
Several levels of regulation control the expression of ptsG. Its expression is triggered by growth on glucose via relief of repression by the Mlc protein, and is also
10 dependent upon cAMP and cAMP receptor protein (CRP) levels [142, 143]. When glucose is not actively transported and PtsG is phosphorylated, Mlc binds to sites upstream of the ptsG promoter, inhibiting transcription. Upon active glucose transport by
PtsG, Mlc is inactivated by sequestration to the membrane via binding to dephosphorylated PtsG. The interaction between PtsG and Mlc is mostly enacted via the
EIIB domain of PtsG. However, the Mlc-EIIB interaction is not fully sufficient for Mlc inactivation. Sequestration to the membrane via the linker domain and last transmembrane domain of PtsG is also required [157]. Negative regulation of ptsG also occurs under conditions of glucose-phosphate stress; posttranscriptional regulation is mediated by the small regulatory RNA (sRNA) SgrS [173]; and the small protein SgrT, encoded by SgrS, posttranslationally inhibits PtsG transport activity [11, 111, 175].
While PtsG is the main glucose transporter of the cell, it is also normally capable of transporting the nonmetabolizable glucose analog α-methylglucoside (αMG), L- sorbose, and glucose derivatives such as 1-thio-glucose and 5-thio-glucose. PtsG typically has a very low affinity for mannose and its nonmetabolizable analog 2- deoxyglucose (2DG). Additionally, mutations that broaden PtsG substrate specificity have been described, allowing transport of glucosamine, mannitol, and ribose [42, 53,
187].
1.3.2 The broad substrate transporter EIIABCDMan (ManXYZ)
Named for its ability to transport mannose, ManXYZ (EIIABCDMan) actually transports a broad range of substrates including 2DG, glucose, fructose, glucosamine, and
N-acetylglucosamine [129]. This EII is encoded by manXYZ and composed of three polypeptides: EIIABMan (encoded by manX), which is a cytoplasmic protein containing
11 the EIIA and EIIB domains fused by a linker, EIICMan, and EIIDMan; these proteins are encoded by manY and manZ, respectively, and form the EIICDMan integral membrane permease [145]. In addition to transporting carbohydrates, ManXYZ, specifically the
EIICMan-EIIDMan components, is utilized by lambda phage for DNA injection [45].
As with ptsG, manXYZ is subject to transcriptional control by CRP:cAMP and
Mlc [141] as well as posttranscriptional control by SgrS under glucose-phosphate stress
[149, 150]. The sRNA DicF also negatively regulates manXYZ, which is interesting given DicF is encoded on a cryptic lambdoid prophage [4].
1.3.3 The N-acetylglucosamine transporter EIICBANag (NagE)
The N-acetylglucosamine transporter NagE (EIICBANag) belongs to the same family of PTS transporters as PtsG based on sequence alignments; these proteins share
61% similarity and 40% identity at the amino acid level. NagE is organized slightly differently than PtsG; though it also consists of three EII domains: EIIC, EIIB, and EIIA, in NagE they are linked into a single polypeptide [138, 145].
Despite its homology to PtsG, NagE is incapable of transporting glucose [65].
However, a hybrid composed of the EIICGlc and EIIBNag domains fused at the identical
LKTPGRED linker motif shared between PtsG and NagE was able to transport glucose and N-acetylglucosamine suggesting there are substrate specificity determinants in both of these domains [73, 111].
The regulation of these two transporters is similar as well. While NagE is also regulated by CRP:cAMP, it is also transcriptionally repressed by the Mlc homolog NagC.
Mlc and NagC are 40% identical with 70% similarity and bind similar operator sequences. Upon mutating both of the Mlc binding sites upstream of ptsG, they could be
12 converted into NagC binding sites allowing NagC to repress ptsG, blinding it to Mlc regulation [39, 137]. At the level of transport activity, while PtsG is strongly repressed by SgrT, NagE and the EIICGlc - EIIBNag hybrid are only transiently inhibited [111].
These data highlight how small differences in two homologous proteins can account for a remarkable amount of specificity.
1.4 Glucose-phosphate stress
Though the term “glucose-phosphate stress” had not yet been coined, the inability of E. coli to utilize the glucose analog alpha-methyl glucoside (αMG) as a carbon source was first observed in 1932 when various substituted sugars were tested for their abilities to be fermented by bacteria. Because αMG could be fermented by Bacterium aerogenes
(Enterobacter aerogenes) but not Bacterium coli (Escherichia coli), it was subsequently used to differentiate the two species [94]. In 1953, S.D. Wainwright further characterized the bacteriostatic effects of αMG in E. coli and proposed that αMG interfered with the phosophofructokinase reaction of glycolysis [177, 178].
Studies using αMG to determine the substrates of various sugar permeases in E. coli revealed that αMG competes with glucose for transport [26], is phosphorylated upon entry into the cell whereupon it accumulates as αMG-6-phosphate (αMG6P), but is not metabolized and cannot support cell growth [60]. Later works characterizing phosphoglucose isomerase (pgi) and phosphofructokinase (pfkA) mutants showed they block glycolytic flux in a manner similar to αMG and that this blockage also causes accumulation of phosphosugars, namely glucose-6-phosphate and fructose-6-phosphate
[51, 90, 123]. Interestingly, the Aiba group discovered that the accumulation of these sugar phosphates resulted in the degradation of the ptsG mRNA, encoding the glucose-
13 specific PTS transporter. This was suggested to be a posttranscriptional effect since inactivating the endoribonuclease RNaseE could reverse ptsG mRNA degradation [90,
123]. In 2004, Vanderpool and Gottesman discovered this ptsG mRNA degradation was due to posttranscriptional regulation by the small RNA SgrS. They found SgrS expression relies upon the transcriptional activator SgrR, which is induced by αMG, and that SgrS helps cells recover from αMG-mediated growth inhibition – a phenomenon they dubbed glucose-phosphate stress [173].
Glucose-phosphate stress can also be induced by the glucose analog 2- deoxyglucose (2DG) and was first observed to inhibit growth in E. coli and other bacteria in 1933; this analog differed from αMG in that no species able to ferment αMG was able to ferment 2DG [95]. Later studies found that 2DG accumulates in the cell as 2DG-6- phosphate, but does not inhibit growth when co-incubated with glucose, suggesting the two substrates do not compete for transport [36]. Indeed, 2DG is primarily transported through the ManXYZ PTS, not the major glucose PTS – PtsG, but is still capable of inducing the glucose-phosphate stress response [65, 150, 165]. In fact, a ptsG manXYZ double mutant is resistant to stress, suggesting that these transporters are involved in importing stress-inducing substrates [150]. Interestingly, when cells were simultaneously exposed to 0.1% 2DG and 0.1% αMG, they were completely unable to recover, even with an intact glucose-phosphate stress response; this suggests 2DG and αMG may elicit stress via different mechanisms (Bobrovskyy and Vanderpool, unpublished). Other analogs such as Methyl N-acetyl-α-glucosaminide, a derivative of N-acetylglucosamine, were not observed to cause growth inhibition or induce the stress response (Lloyd and
Vanderpool, unpublished).
14 Efflux also plays an important role in glucose-phosphate stress. It has long been suggested that while αMG accumulates in the cell, it is also actively pumped out of the cell by an unknown permease, and that efflux must follow dephosphorylation of the accumulated αMG6P by an unidentified phosphatase - since the charged phosphate group causes sugars to be retained in the cell [51, 68, 183]. Work from our group helped to identify the phosphatase responsible for dephosphorylating αMG6P – YigL. Production of YigL is promoted by the glucose-phosphate stress response as SgrS actively stabilizes the yigL mRNA by inhibiting RNAse E degradation [134]. While the efflux pump that acts downstream of YigL has yet to be identified, my work suggests the multidrug efflux pump TolC may be involved. Additionally, the sugar efflux pump SetA, which is cotranscribed with SgrS under glucose-phosphate stress, is involved in stress recovery, as a setA mutant exhibits a growth defect under stress conditions. However, in vivo radiolabled αMG efflux assays demonstrated SetA is not the major efflux pump responsible for αMG efflux and may be acting by a different mechanism to promote growth during stress [164].
The exact nature of glucose-phosphate stress remains unclear. It has been suggested that the accumulation of phosphosugars in itself is toxic [41, 51, 75, 90, 123,
185]. However, supplying cells exposed to αMG or harboring mutations in glycolytic enzymes with phosphosugar intermediates downstream of the metabolic block (such as glucose-6-phosphate, fructose-6-phosphate, and fructose-1,6-bisphosphate) relieves growth inhibition and stress, even in an sgrS mutant [90, 151]. Earlier glycolytic intermediates rescue growth more effectively than downstream intermediates, to the point in which adding pyruvate to sgrS mutants under stress causes lysis [151]. My work has
15 shown that the addition of intermediates such as glucose-6-phosphate does not interfere with αMG uptake, which demonstrates that growth recovery can occur even under αMG accumulating conditions [151]. These studies suggest phosphosugars per se do not cause glucose-phosphate stress, but it is instead due to the depletion of critical glycolytic intermediates - specifically depletion of phosphoenolpyruvate (PEP), the phosphate donor expended during PTS sugar transport. Consistent with this hypothesis, PEP synthase
(ppsA) mutants that are unable to convert pyruvate to PEP are more sensitive to αMG and conversely, overproduction of PEP synthase rescued growth inhibition in a sgrS mutant
[16, 151]. In contrast to its effects in combination with αMG, pyruvate (as well as gluconate) was observed to help cells resist growth inhibition by 2DG, further suggesting these two analogs cause stress by different mechanisms [36].
It remains unclear as to how glucose-phosphate stress occurs in nature, particularly as it pertains to αMG. Could αMG itself be a natural cause of glucose- phosphate stress? αMG has long been synthesized in labs studying sugar transport and metabolism by bacteria, but it has also been detected in environmental water samples
[140]. Whether this is due to decades of experimental waste being dumped into sewage systems or because αMG can be found in nature is unclear. Furthermore, while αMG is non-metabolizable in E. coli, it can be metabolized by Klebsiella [139] and Enterobacter
[94], however species of Klebsiella and Enterobacter also encode SgrR and SgrS homologs, suggesting that they still encounter glucose-phosphate stress despite their ability to break down αMG [71].
16 1.4.1 Induction of the stress response by the transcription factor SgrR
The glucose-phosphate stress response is controlled by the transcription factor
SgrR. Initially annotated as a periplasmic solute-binding protein, it also contained helix- turn-helix motif suggestive of DNA binding. Because of its close proximity to sgrS, it was suspected to instead act as a transcriptional regulator. Northern blot analysis revealed that wild-type cells exposed to αMG expressed high levels of SgrS, but ΔsgrR cells failed to induce SgrS [173].
Equipped with a C-terminal ligand binding domain and an N-terminal DNA binding domain, SgrR senses stress, presumably through a small molecule ligand, and activates transcription of the divergently transcribed sgrS, setA operon. SgrR is also capable of negatively autoregulating its own transcription, both in the absence and presence of stress
[173, 174].
Identifying the ligand that binds SgrR during glucose-phosphate stress would elucidate the signal of and therefore the nature of the stress. Despite being a cytoplasmic protein, SgrR is extremely difficult to purify and previous studies have been unsuccessful at identifying small molecule binding partners. Although enough protein was purified to perform gel-shifts and verify that SgrR binds to sgrS promoter DNA, gel shift reactions were unaffected by incubation with glucose-6-phosphate, suggesting this may not be the small molecule ligand. To circumvent these technical biochemistry issues, Vanderpool and Gottesman began identifying genes in the SgrR regulon, which may be functionally and physiologically related and give clues as to the identity of the stress signal. SgrR was found to transcriptionally activate ydfZ, now called alaC [174]. AlaC is a transaminase that converts pyruvate and glutamate into alanine and α-ketoglutarate. AlaC could
17 respond to elevated pyruvate concentrations under stress conditions, since excess pyruvate lyses cells unable to respond to stress, and an imbalanced PEP to pyruvate ratio is thought to be central to glucose-phosphate stress [151]. However, alaC mutants are not sensitive to αMG, though alaC mutants were never tested for exacerbated sensitivity to αMG in an sgrS mutant background [86].
1.4.2 The small RNA SgrS
The 227 nucleotide sRNA SgrS, then called RhyA, was discovered in a 2003 global co-immunoprecipitation analysis aimed at identifying small RNA binding partners of the RNA chaperone Hfq [189]. The physiological effects of SgrS, however, had already been reported in 2001 when the Aiba group noticed posttranscriptional regulation of the glucose permease PtsG under glucose-phosphate stress conditions [90]. In 2004 a study by Vanderpool and Gottesman combined these independent observations and reported that sgrS expression was controlled by the transcriptional activator SgrR and induced by αMG-mediated glucose-phosphate stress, which subsequently led to SgrS- dependent degradation of the ptsG mRNA. Additionally, they observed that ectopic SgrS overexpression inhibited growth on glucose as a sole carbon source and that ΔsgrS cells were more sensitive to growth inhibition by αMG. This relationship to sugar stress led to the renaming of RhyA to SgrS for sugar transport related sRNA.
SgrS riboregulates multiple targets to ameliorate glucose-phosphate stress. Two of its major negative targets include the PTS transporters ptsG and manXYZ. SgrS inhibits translation of the ptsG mRNA by directly base pairing with the RBS, thereby preventing ribosome loading. This repression does not require, but is followed by degradation of the sRNA-mRNA complex by the RNase E degradasome. In this way,
18 SgrS prevents synthesis of additional glucose/αMG transporters and therefore prevents further influx of non-metabolizable sugars [85, 173, 174]. Similarly, SgrS inhibits the translation of manXYZ, albeit by a different mechanism. SgrS pairs within the manX coding region to prevent translation, but also pairs within the manX-manY intergenic region – both sites are independently sufficient for individual manX and manYZ regulation, but synergistic binding of both sites is required for optimal stress recovery
[149]. It has also been discovered that in regulating manX, SgrS serves a reversed role acting as a guide for Hfq, which directly represses translation by competing with ribosomes for binding [4]. As with PtsG, by inhibiting synthesis of ManXYZ SgrS prevents further influx of the stress-inducing substrates 2DG and αMG giving cells time to recover their growth [150].
While it is important for cells to limit further influx of non-metabolizable sugars under stress, it is also critical to efflux sugar phosphates that have already accumulated.
The only positively regulated target of SgrS is yigL, which encodes a phosphatase responsible for dephosphorylating αMG6P and 2DG6P into uncharged substrates for efflux [97, 134]. SgrS stabilizes the processed yigL transcript by masking RNase E cleavage sites, thereby enhancing translation. YigL is required for optimal recovery from glucose-phopshate stress; fast and efficient αMG efflux depends on YigL, and like sgrS mutants yigL mutants are not only sensitive to αMG and 2DG, but exhibit growth inhibition on the PTS sugars glucose and trehalose in a pgi mutant background [134].
SgrS-mediated posttranscriptional regulation of ptsG, manXYZ, and yigL is necessary for full growth recovery during glucose-phosphate stress, but is not sufficient when stress is accompanied by low nutrient availability, such as in minimal media [165].
19 This not only supports the notion that metabolite limitation contributes to stress, but also suggests that there may be other SgrS targets involved in rerouting metabolism under stress, particularly when metabolic intermediates are scarce. Work by our group identified four new negatively regulated mRNA targets that may fulfill such roles: asd, adiY, folE, and purR. When each of these targets was ectopically overexpressed under
PEP-limiting conditions via a mutation in PEP synthase (ppsA), cells were more sensitive to glucose-phosphate stress [16]. This suggests the activities of these gene products are deleterious during stress, particularly when pyruvate accumulates or PEP is depleted.
How these proteins contribute to stress is unclear, however regulation of asd, which encodes Aspartate semialdehyde dehydrogenase, may increase intracellular pools of apartate. Aspartate supplementation can partially rescue ppsA growth defects as it is converted to OAA by aspartate transaminase (aspC), which can subsequently be converted to PEP by PEP carboxykinase (pck) [93]. Pck has also been shown to modulate glycolytic flux and balance PEP to pyruvate ratios when PTS sugar transport is inactivated, thereby replenishing intermediates that rely on PEP [50, 119].
1.4.3 The small protein SgrT
In addition to modulating the translation of multiple mRNA targets using a conserved seed region at its 3’ end, SgrS is in itself an mRNA, encoding the small, 43- amino-acid protein SgrT within the 5’ region. However, the open reading frame is not encoded in all sgrS alleles. When a variety of enteric species were examined for the presence of SgrS and SgrT homologs, it was found that not every species harboring an
SgrS homolog encoded SgrT; for example, in Yersinia pestis and Escherichia coli
O157:H7 SgrT is absent. Among species that encoded both SgrS and SgrT, the SgrS
20 base pairing region was highly conserved while the SgrT ORF was variable [71].
Furthermore, of the enteric bacteria that encode an SgrT homolog, not all species produce
SgrT protein. Some species, like E. coli K12 and E. carotovora have an inhibitory stem- loop that sequesters the SgrT ribosome binding site, preventing translation [71]. This stem-loop was demonstrated to inhibit SgrT translation in E. coli K12 and mutations disrupting the stem-loop restored translation. Interestingly, while E. carotovora also has a predicted inhibitory stem-loop, its SgrT allele could functionally complement an sgrST mutant in E. coli to abrogate glucose-phosphate stress, suggesting this secondary structure may be subject to regulation - perhaps by yet another sRNA [71, 176].
Salmonella enterica serovar Typhimurium produces functional SgrT from its chromosome; experiments investigating the contributions of SgrT to the glucose- phosphate stress response either made use of this Salmonella allele, or an E. coli K12 allele containing a heterologous RBS [11, 111, 175, 176].
Unlike the dual-function sRNA RNAIII, the base pairing and open reading frame regions do not overlap in SgrS and are spatially distinct. Independent ectopic expression of either the SgrS base pairing region or the SgrT protein rescues αMG-mediated growth inhibition and also results in growth inhibition on glucose as a sole carbon source. While these two components act in the same pathway, they do so at different levels: SgrS base pairing only affects ptsG mRNA stability and subsequent translation, while SgrT affects
PtsG activity; SgrT was shown to inhibit inducer exclusion when cells were grown with both glucose and lactose [175].
Since SgrS is co-degraded with its targets during riboregulation, it was unclear how it could serve as a substrate for translation to produce SgrT, and how translation
21 would then affect riboregulation since the ORF and base pairing regions are only separated by 15 nucleotides. Work from our lab using Salmonella SgrS determined that riboregulation begins to affect ptsG mRNA levels within 2 minutes of glucose-phosphate stress and only after 40 minutes is SgrT protein detectable. Mutations that prematurely terminate SgrT translation had little effect on SgrS riboregulation, however base pairing mutations markedly increased SgrT protein levels. Similarly, SgrT protein levels increased in hfq mutants unable to perform riboregulation. These data support a model in which SgrS is co-degraded with mRNA targets leaving fewer SgrS molecules available for translation. Once mRNA targets have been depleted, larger pools of SgrS are available to produce SgrT later in the stress response [11]. Interestingly, SgrT protein levels decreased again after 140 minutes implicating a possible mechanism for posttranslational regulation, possibly affecting protein stability. This stability also appears to be PtsG dependent, as SgrT protein is undetectable in a ptsG mutant [11]. See
Figure 1.1 for a model of the glucose-phosphate stress response.
1.5 The small RNA DicF
DicF was discovered in the late 1980s when it was serendipitously cloned into a plasmid and found to cause cell filamentation in trans. This was a surprise, as the researchers were endeavoring to create a lacZ fusion to the 5’ end of its downstream neighbor dicB, which encodes a protein known to cause filamentation, and this fusion excluded the minimal region of dicB required for filamentation. Because there was no apparent open reading frame in the cloned region, and subsequent deletion mapping revealed a region as little as 65 nucleotides could facilitate filamentation, the authors reasoned that the effect was due to an RNA species and not a protein [19].
22 The dicBF operon is encoded on the lambdoid cryptic prophage Qin and is transcribed with four other uncharacterized protein-coding genes: the promoter-proximal ydfA, ydfB, ydfC, and ydfD, which is encoded downstream of dicB. The small protein
DicB is the only other characterized member of the operon and causes filamentation by inhibiting cell division through interaction with MinC [78, 98, 125] and ZipA [79]. The dicBF operon undergoes RNase E and RNase III processing to yield the functional DicF sRNA [46]. RNase III carries out an initial processing event generating a ~183- nucleotide precursor RNA that undergoes subsequent RNase E-mediated cleavage to generate a mature 53-nucleotide DicF. Recent work suggests the enolase component of the degradosome stabilizes mature DicF during RNase E maturation, particularly under anaerobic conditions [127].
1.5.1 Targets of DicF regulation
The first established target of regulation, and arguably the most dramatic, is ftsZ
[10, 167]. By posttranscriptionally inhibiting ftsZ translation, Z-ring and septum formation is impaired, halting cell division. This target accounts for the classic DicF filamentation phenotype. Additional targets were identified using both computational prediction and RNA-seq techniques; these are xylR, encoding a transcription factor that controls xylose utilization, and pykA encoding pyruvate kinase. DicF is known to bind
Hfq [189] and was subsequently shown to require Hfq for efficient target regulation. All three aforementioned targets are regulated via canonical RBS occlusion in which Hfq acts as a chaperone [10], however recent work has shown another weaker target, manX, is regulated by a noncanonical “role-reversal” mechanism in which Hfq, not DicF, binds near the RBS to inhibit translation [4]. Interestingly, though the degradosome is required
23 for DicF processing, it was not shown to be required for DicF target regulation as DicF still inhibits target translation in an rne 131 (degradosome) mutant background [10].
1.5.2 Effects of DicF on E. coli physiology
In addition to causing filamentation through ftsZ regulation, DicF expression inhibits growth and causes bloating in rich LB media. Because DicF also inhibits xylR production, it was unsurprising that ectopic DicF expression inhibited growth on xylose as a sole carbon source. This effect was lost in a DicF mutant unable to regulate xylR, but still able to regulate ftsZ. Other mutant DicF alleles that could differentially regulate the three known targets were generated to examine the contributions of each target to growth inhibition. An allele (DicF21) that could regulate xylR, but not ftsZ or pykA, lost the filamentation, bloating, and growth inhibition phenotypes in LB. Another allele (DicF3) that could regulate ftsZ, but not xylR or pykA remained filamented, but no longer bloated, and regained growth. These results suggest there are other uncharacterized targets that contribute to growth inhibition and cell bloating, and that filamentation by ftsZ inhibition is not solely responsible for these effects [10]. Other studies have shown DicF to decrease biofilm formation, swimming, and swarming motility, however the effects appear to be indirect [8].
The dicBF locus is conserved in 17 of 27 E. coli and Shigella genomes analyzed by Balasubramanian et al. This locus was also found encoded within Qin-like and lambdoid prophages. Interestingly, various pathogenic E. coli genomes encode multiple copies of this operon [10]. These data suggest the conserved maintenance of this operon may be beneficial under certain conditions. Cryptic prophages have been shown to confer resistance to various environmental conditions [179], and filamentation can offer
24 protection from stresses and extracellular assaults [81]. Why this particular sRNA has been maintained in the chromosome remains elusive.
1.6 Aim of the study
Stress responses and their effects on gene expression are important facets of physiology across all domains of life. Some stress responses are mediated through small
RNA (sRNA) regulators, which base pair with mRNA targets and either positively or negatively influence their translation. In bacteria, sRNAs were once considered “non- coding RNAs;” however, a number of these RNAs have been found to encode functional proteins as well and therefore have two functions. One such dual-function sRNA is SgrS and its protein product is SgrT. Both SgrS and SgrT are expressed in Escherichia coli under conditions of glucose-phosphate stress in which non-metabolizable phosphosugars accumulate in the cell and inhibit growth. Our lab has shown that the SgrS base pairing function mitigates this stress by inhibiting synthesis of the major glucose transporter PtsG through translational repression of the ptsG mRNA. SgrT relieves glucose-phosphate stress independently of SgrS base pairing and its function is thought to inhibit preexisting
PtsG transporters posttranslationally, as SgrT negatively affects PtsG transport activity and its overexpression inhibits growth when glucose is the sole carbon source. This work will demonstrate whether SgrT targets PtsG, and will define in detail the determinants and physiological consequences of this regulation as it relates to glucose-phosphate stress relief.
Trans-acting sRNAs typically have important roles in combating stress, yet the sRNA DicF causes severe growth defects in E. coli. Whether there are conditions in which DicF is beneficial remains unclear, however learning more about the nature of and
25 contributors to DicF-mediated growth inhibition may shed light on this question. Work from our lab showed DicF mutants that differentially regulate known mRNA targets restore growth, suggesting there are still unidentified targets that contribute to growth inhibition. This study will identify new targets of DicF riboregulation and elucidate factors that contribute to its effects on cell growth and morphology.
26 1.7 Figures
Figure 1.1 Current Model of the Glucose-Phosphate Stress Response. The PTS transporters PtsG and ManXYZ transport the non-metabolizable analogs αMG and 2DG into the cell generating αMG6P and 2DG6P. Accumulation of these phosphosugars activates SgrR, which triggers synthesis of SgrS. Early SgrS riboregulation posttranscriptionally inhibits translation of the ptsG and manXYZ transporter mRNAs and targets them for degradation by RNaseE and the degradosome, thereby halting further tranporter synthesis. SgrS riboregulation also stabilizes the yigL mRNA, which enhances production of the YigL phosphatase; this dephosphorylates αMG6P and 2DG6P and primes them for efflux via an unknown channel. Later in the stress response, pools of SgrS become available for translation to produce the SgrT protein. SgrT then binds and inhibits the transport activity of preexisting PtsG transporters, thereby preventing further αMG influx.
27 Chapter 2: Materials and methods
2.1 Strains and plasmid construction
All strains and plasmids used in this study are summarized in Table 2.1 and oligonucleotides used to construct strains and plasmids are detailed in Table 2.2. For the strains and plasmids described in chapter 3 the pBR322-derivative plasmids harboring
SgrT used in this study were previously described [176]. To create the pZA plasmid derivatives of pZA31-R [106], wild-type E. coli MG1655 ptsG was cloned into the
BamHI and NdeI sites of the plasmid and mutants were created using QuikChange mutagenesis (Agilent Technologies). All Δlac strains are derivatives of DJ480 (D. Jin,
National Cancer Institute). CL104 was created by P1 transducing an sgrS::tet mutation
into a strain containing a PsgrS-lacZ transcriptional fusion (CV5202). CL108 was subsequently created by transducing a ptsG::kan mutation from the Keio collection [5] into CL104. Strain CL113 was constructed by P1 transduction of galP::kan (from the
Keio collection) and manXYZ::cat cassettes into strain CS216 (sgrS::tet, mal::lacIq+).
CL174, CL175, and CL188 are all derivatives of CL113 where kanamycin cassettes were removed using the FLP-mediated site-specific recombination methods described in [40].
The PtsG-NagE hybrid created in CL175 was generated by PCR amplifying the first 1050 nucleotides of EIICGlc linked to an upstream kanamycin cassette from the chromosome of the ycfH::kan Keio collection mutant and recombining this linear PCR product into the
NM300-1 strain (which carries a mini-λ encoding λ Red functions) [27] via transformation at the nagE locus, then P1 transducing the hybrid into CL174.
For strains and plasmids described in chapter 4, The CS123 strain carries the
sgrS1 mutant allele unable to regulate ptsG translation [176]. The PsgrS-lacZ
28 transcriptional reporter fusion [150, 164]was inserted into the λattB chromosomal site of the Δlac strain CS123 to create CL109 [153]. DJ480 (D. Jin, National Cancer Institute) served as our wild type strain from which CL114 (tolC::kan) and CL115 (yigL::kan) were created by transducing P1 lysates grown from the keio collection tolC::kan and yigL::kan mutants. CS104 [176], a markerless sgrS deletion mutant was P1 transduced with keio- derived tolC::kan and yigL::kan mutants to yield CL116 and CL117, respectively. The
PsgrS-lacZ transcriptional reporter fusion [150, 164] was inserted into the λattB chromosomal site of CS104 to generate CL122. Strain BAH100 harbers a PsgrS-lacZ transcriptional reporter fusion and was previously described [150, 164]. This fusion was
transduced into CL114 and CL115 to create CL118 and CL119, respectively. The PsgrS- lacZ was also transduced in to the λattB sites of CL118 and CL119 to generate CL120 and CL121, respectively. CL139 was created by inserting a cat cassette into the tolC locus of NM300-1 via λred recombination [186]; a P1 lysate was grown on this strain and transduced into CL121 to yield CL142.
Strain CL190 that was used in chapter 5 for ITS titration experiments and that served as the DicF suppressor parent strain was made from by transducing the tetR::spec allele (from JH111 [150]) into the λattB site of DB229 [11]. CL191 was made from
CL190 by P1 transduction with a mdfA::kan lysate grown from the keio collection [5].
CL192 (mdfA::FRT) was subsequently produced from CL191 by flipping out the kan cassette flanked by FRT sites using Flp recombinase provided in trans on the pCP20 plasmid [25]. CL197 and CL201 were created by transducing in an ahpC::kan allele and ybjH::kan allele, respectively, from the keio collection into CL190 by P1 transduction.
All suppressor strains (DSup1-10, 13, 14) were created by streaking CL190 harboring
29 Plac-dicF and Ptet-dicF plasmids [10] onto fresh LB plates containing antibiotics, then selecting independent colonies to be streaked on LB containing 1 mM IPTG and 50ng/ml aTc plus antibiotics. Suppressors were allowed to grow at room temperature for a few days, and then were restreaked on LB containing antibiotics, IPTG, and aTc. P1 lysates from the following keio collection alleles: mdfA::kan, ahpC::kan, ybjH::kan, and fdfH::kan were transduced into DB166 [11] to yield CL202, CL203, CL204, and CL205.
For chromosomal translational –‘lacZ fusions, sequences of the mdfA (O-CL268/269
[long], O-CL268/280 [medium], O-CL268/281 [short/BP-], rplU (O-CL245/246), rplN
(O-CL247/248), ahpC (O-CL249/250), rpoS (O-CL251/252 [long], O-CL251/255
[short]), ftsN (O-CL253/254), bolA (Oi-CL256/257), amiC (O-CL258/259), nlpD (O-
CL260/261), zapB (O-CL262/263), rlpA (O-CL264/265), and ftsA (O-CL266, 267) genes were amplified with the indicated oligonucleotides and intedgrated in to the strain
PM1205 [115] to create strains CL198, CL199, CL200, CL206, CL207, CL208, CL209,
CL211, CL210, CL211, CL212, CL213, CL214, CL215, CL216, and CL217. All ITS
plasmids were gifts from the Massé group [99].The PMdfA (pT7-5/mdfA-His6 ) plasmid and corresponding vector were gifts from the Bibi group [107].
2.2 β-galactosidase assays
For the indirect transport assays described in chapter 3 CL104 and CL105 strains harboring pBRCS12 or pBRCS1 plasmids were grown overnight in TB with ampicillin and subcultured 1:100 into TB medium with 1 mM IPTG to induce SgrT. Cells were
grown to an OD600 of 0.5, split and either stressed with 0.5% αMG, 0.2% 2DG or left unstressed. Samples were taken after 120 minutes then Miller assays performed [120].
For CL108 strains harboring pBRCS12 or pBRCV7 and pZACL1, pZACL2, or pZACL3
30 plasmids, the same protocol was used and PtsG synthesis was induced with 50ng/ml of aTc.
For Miller assays described in chapter 4 WT (BAH100), sgrS (CL122), tolC
(CL118), yigL (CL119), sgrS tolC (CL120), sgrS yigL (CL121), and sgrS tolC yigL
(CL142) strains were grown overnight in TB, then subcultured 1:200 and grown to an
OD600 of 0.1. Then cultures were split, with half receiving 0.5% αMG to induce the SgrS stress response and the other half receiving an equivalent volume of ddH2O. Samples were taken after 120 minutes and β-galactosidase activity measured.
For Miller assays used to measure posttranscriptional regulation in chapter 5 strains were grown overnight in TB then subcultured 1:100 the following morning and lacZ reporter fusions induced with 0.02% L-arabinose for 60 minutes after which DicF expression was induced with β-galactosidase activity was assayed after 45 minutes of plasmid-borne dicF expression with 1 mM IPTG. Specific activities were quantified in
Miller units and normalized to vector controls to generate percent relative activity.
2.3 [14C]αMG transport and efflux assays
For transport assays described in chapter 3 CL113 cells with pBRCS12 (vector), pBRCS1 (SgrT), or pCV05 (SgrS base pairing) were grown overnight in 0.4% M63
glycerol with ampicillin then subcultured 1:200 in fresh M63 glycerol to an OD600 of 0.2 and expression induced with 0.1 mM IPTG for 5 min. Cultures were then subjected to radiolabeled uptake assays as described previously [53], with the following modifications. Cultures were placed on ice, pelleted at 4°C, washed once with 10 ml of
M63 salts, and then washed again in 6 ml of M63 salts. The cells (0.3 ml) were diluted in
0.7 ml of M63 salts and kept on ice until the assay was started. The assay was initiated by
31 shifting cells to room temperature and adding 10 μl of 10 μM uniformly radiolabeled
[14C]αMG (methyl-α-D-glucopyranoside; 3 μCi/ml; American Radiolabeled Chemicals).
0.1 ml aliquots were withdrawn at various time intervals and transport quenched by dilution into 4ml of ice-cold M63 salts plus 0.02% glucose. Samples were then vacuum filtered (Thermo Fisher Scientific; 25 mm; 0.45-μm pore size) and washed with 20 ml ice-cold 0.05% NaCl. For transport assays described in chapter 4 wild type (DJ480) or sgrS mutant (CS123) strains were grown overnight and subcultured in fresh LB medium as described above for growth experiments. Samples were then split in half, and
1.38 μM glucose-6-phosphate was added to one half only. Immediately following addition of [14C]αMG, aliquots of 0.1 ml were withdrawn at 1, 5, 10, 15, and 20 min and then diluted in 4 ml of ice-cold M63 salts plus 0.02% glucose. These samples were vacuum filtered (Thermo Fisher Scientific; 25 mm; 0.45-μm pore size) and washed with
20 ml ice-cold 0.05% NaCl. Radioactivity of the cells was then counted via liquid scintillation.
Efflux assays were conducted in a similar manner to transport assays. Strains
(CL1771, CL1821, CL1811, CL1841, NC118, NC117) were grown overnight in M63 glycerol (0.4%) with antibiotics at 37°C. After diluting the strains (1:100) in 5mL M63
glycerol to an OD600 of 0.1. A 1 ml aliquot was harvested to which we added 3.3μM
[14C]-αMG, which was incubated for 20 minutes at room temperature. Efflux was initiated by by diluting samples into 100ml of M63 salts plus 0.4% glycerol. 4mL samples were harvested at times 0, 2, 9, 15, 20, 30 minutes post efflux, by filtering through 25 mm, 0.45 μm MCE filters in a vacuum manifold. Radioactivity retention was measured via liquid scintillation.
32 2.4 Immunostaining and superresolved single-fluorophore microscopic imaging
As describe in chapter 3 CL108 cells carrying 3X-FLAG tagged SgrT (pBRCS1)
in the presence and absence of ptsG were grown to OD600 ~0.3, and then induced for SgrT and PtsG expression by 50 µM IPTG and 50 ng/mL anhydrous tetracycline respectively for 30 minutes. Cells were collected and fixed with 4% formaldehyde and immobilized on the Lab-TekTM chambered coverglass coated by poly-L-lysine (Sigma-Aldrich P8920) at room temperature. Then cells were washed by 1X PBS for three times, then were permeabilized by 10mg/ml lysozyme (Sigma-Aldrich L6876) dissolved in 25 mM Tris-Cl
(pH=8), 10 mM EDTA and 50 mM glucose for 30 minutes at room temperature. Cells were washed by 1X PBS three times again, and were treated with 3% BSA in 1X PBS for one hour at room temperature. Then cells are incubated with the primary anti-FLAG antibody (from mouse) in 0.3% BSA/1X PBS for one hour at room temperature. Cells were washed three times with 0.3% BSA in 1X PBS, and then incubated with Alexa 647 labeled secondary antibody in 0.3% BSA/1X PBS for one hour at room temperature.
Then cells were washed three times with 0.3% BSA in 1X PBS. Super-resolution imaging was performed as previously described [47] on an inverted microscope excited with a 647 nm laser and a 405 nm laser. The emission was separated and collected by a dichroic mirror and notch filters for 647 nm laser, and was recorded by an EMCCD camera. A cylindrical lens was inserted in the emission path for 3D imaging. Each
STORM image was reconstructed by about 2~30,000 frames with 30 ms exposure.
Samples are all imaged in the imaging buffer (10 mM NaCl, 50 mM Tris (pH=8), 10% glucose, pyranose oxidase (Sigma-Aldrich P4234, final concentration 1.11 U/mL) and
33 catalase (EMD Millipore 219001, final concentration 10 KU/mL)). Image reconstruction was performed as previously described [47].
2.5 Growth assays
Bacteria were cultured in Luria-Bertani (LB) medium at 37°C unless otherwise specified. For experiments in chapter 3 investigating the overexpression of SgrT on various carbon sources CV104 cells harboring pBRCS12 or pBRCV7 plasmids were plated on minimal M63 salt agar plates containing 0.2% glucose, N-acetylglucosamine
(GlcNAc), fructose, trehalose, or mannose plus ampicillin and 1 mM IPTG to induce
SgrT. For growth curve experiments in minimal media CL174, CL175, and CL188 cells containing pBRCS12 or pBRCS1 plasmids were grown overnight in M63 with 0.4% glycerol plus ampicillin then subcultured 1:200 in M63 with 0.2% glucose plus ampicillin and 1 mM IPTG to induce SgrT. For growth curves examining growth with or without addition of lactose under glucose-phosphate stress CS136 cells harboring pHDB3 or pBRCV7 were grown as previously described [175]. Growth curve experiments conducted past 12 hours were performed in a plate reader. Independent triplicate cultures were grown overnight in M63 glycerol (0.4%), then subcultured 1:200 in either 0.2% glucose or 0.2% GlcNAc and grown for one hour, then 0.2 ml was transferred into the wells of a 96-well plate and optical density monitored for 24 hours. Experiments investigating the sensitivity of ptsG mutants to SgrT regulation were performed using
MacConkey agar plates containing 1 mM IPTG to induce sgrT, 50ng anhydrous tetracycline (aTc) to induce ptsG, 0.5% αMG to induce the stress response, 100mg/ml ampicillin and 25mg/ml chloramphenicol to select for the SgrT and PtsG-harboring plasmids, respectively, and 1% lactose.
34 For growth experiments in chapter 4 examining the effects of sgrS, tolC, and yigL mutations on growth and glucose-phosphate stress, cells were grown on LB media with or without 0.5% αMG.
Growth experiments conducted in chapter 5 monitoring DicF suppressor growth
using a plate reader involved ectopically expressing DicF from two plasmids (Plac-dicF and Ptet-dicF) from cells grown in LB with antibiotic overnight, then subcultured 1:200 in
LB and grown for one hour. DicF was induced with 50 ng aTc and 1 mM IPTG for 45 minutes, then aliquots of cells were transferred to a 48 well plate and grown in a plate reader with continuous shaking (BMG LABTECH FLUOstar Omega). For growth curves conducted by hand, the same procedure was followed except cells were never transferred to a plate. For alkaline pH growth experiments conducted on solid media, media was prepared by buffering LB with 70 mM 1,3-bis[tris(hydroxymethyl)- methylamino]propane (Bistris propane or BTP) and brought to the desired pH with HCl.
Antibiotics and 1 mM IPTG were added after autoclaving. Overnight cultures were
spotted directly onto plates then diluted to an OD600 of 0.01 and spotted as well.
Subsequent 1:100 serial deletions were produced and spotted for each strain at each pH
(7.0, 7.5, 8.0, 8.5, and 9.0).
2.6 Whole-genome sequencing and data analyses
Whole genome sequencing of the DicF suppressor strains from chapter 5
(DSup1-10, 13, 14) was conducted at the University of Illinois at Urbana-Champaign
Roy J. Carver Biotechnology Center / W.M. Keck Center. Genomic DNA was harvested using the Wizard® Genomic DNA Purification Kit (Promega) and submitted to the
Bioechnology center for Shotgun Nextera genomic DNA library preparation. Single-end
35 reads were sequenced using the Hiseq 2500 System (Illumina). Sequencing results were analyzed using Breseq [33].
2.7 Microscopy
The light microscopy conducted in chapter 5 was conducted using an EVOS XL light microscope at 40X magnification. Strains were observed after 120 minutes of DicF expression.
2.8 Pulse-chase assay
The pulse-chase assay used in chapter 5 to assess protein synthesis during ectopic
DicF expression was modified from a protocol by Hoffmann et al [69]. DB176 cells were grown overnight in M63 glucose, then subcultured the next day and grown to an
OD600 of 0.2. Plac-DicF was either induced prior to the pulse for 20 minutes or during the pulse with 1 mM IPTG. Cells were then washed with M63 glucose twice then resuspended in 1ml of the same media. The pulse was initiated by the addition of
10μCi/ml [35S] L-methionine with 2 μM cold L-methionine. A 100μl aliquot was taken immediately as a time zero sample. Aliquots were taken subsequently at 10 minute increments for one hour. Samples were added to 1ml of a 1M NaOH solution and incubated at 37°C for 10 minutes. After incubation a 4ml solution of 25% ice cold TCA,
1 mM DTT, and 1 mM cold L-methionine was added to the samples. Samples were kept on ice for 30 minutes and filtered in a vacuum manifold on Whatman fiberglass disks.
Disks were washed with 10ml of 5% TCA and 5ml of 95% ethanol. Disks were dried and radioactivity measured via scintillator.
36 2.9 Tables
Table 2.1 Strains and plasmids used in this study
Strain Description Source Chapter 3 DJ480 MG1655 ΔlacX74 D. Jin (NCI) DJ624 DJ480 mal::lacIq+ D. Jin (NCI) CV104 (DJ624) ∆lacX74 mal::lacIq ∆sgrS::kan [173] CS136 (MG1655) ∆sgrS::kan [176] q+ Δlac; mal::lacI ; PsgrS-lacZ (short CV5202 fusion) C. Vanderpool Δlac; mal::lacIq+; PsgrS-lacZ (short CL104 fusion) (CV5202) sgrS::tet [111] CL105 (CL104) manXYZ::kan [103] CL108 (CL104) ptsG::kan [103] CS216 (DJ624) sgrS::tet C. Wadler CL111 (CS216) galP::kan [103] CL113 (CL111) manXYZ::cat [103] CL113 pCP20 (CL111) galP::FRT [103] CL143 (CL113 pCP20) ptsG::kan [103] CL174 (CL143) ptsG::FRT [103] (CL174) EIICglcNAc::EIICglc (at nagE CL175 locus linked to kan) [103] CL188 (CL113 pCP20) nagE::kan [103] Chapter 4 DJ480 MG1655 ΔlacX74 D. Jin (NCI) DJ624 DJ480 mal::lacIq+ D. Jin (NCI) CS104 (DJ624) clean ΔsgrS (allele sgrS2) [176]
CS123 (DJ480) sgrSG176C,G178C [164]
CL109 (CS123) attB::PsgrS-lacZ [153] CL114 (DJ480) tolC::kan (from Keio collection) This study (DJ480) yigL::kan (from Keio CL115 collection) This study CL116 (CS104) tolC::kan This study CL117 (CS104) yigL::kan This study
(CS104) PsgrS-lacZ (long) (from CL122 BAH100) This study (DJ480) λsgrS-lacZ long fusion BAH100 containing part of sgrR This study
CL118 (CL114) PsgrS-lacZ (long)(BAH100) This study
CL119 (CL115) PsgrS-lacZ (long)(BAH100) This study
CL120 (CL116) PsgrS-lacZ (long)(BAH100) This study
CL121 (CL117) PsgrS-lacZ (long)(BAH100) This study CL142 (CL121) tolC::cat This study
37 Table 2.1 (continued)
Chapter 5 DJ480 MG1655 ΔlacX74 D. Jin (NCI) + (DJ480) ΔaraBAD araC , PBAD::cat- PM1205 sacB::lacZ, mini λTet [115] DB229 (PM1205) ftsZ'-'lacZ [10] (DB229) λattB::lacIq-PN25tetR-specR CL190 (from JH111) This study DSup1 (CL190) mdfA::IS1 This study DSup2-10, 13, 14 (CL190) This study CL191 (CL190) mdfA::kan This study CL192 (CL191 pCP20) mdfA::FRT This study CL197 (CL190) ahpC::kan This study CL201 (CL190) ybjH::kan This study DB166 (DJ480) λattB::lacIq-PN25tetR-specR [10] DB176 (DB166) ΔdicF CL202 (DB166) mdfA::kan This study CL203 (DB166) ahpC::kan This study CL204 (DB166) ybjH::kan This study CL205 (DB166) fdfH::kan This study CL198 (PM1205) mdfA'-'lacZ (long) This study CL199 (PM1205) mdfA'-'lacZ (medium) This study CL200 (PM1205) mdfA'-'lacZ (short/BP-) This study CL206 (PM1205) rplU'-'lacZ This study CL207 (PM1205) rplN'-'lacZ This study CL208 (PM1205) ahpC'-'lacZ This study CL209 (PM1205) rpoS'-'lacZ (long) This study CL210 (PM1205) ftsN'-'lacZ This study CL211 (PM1205) rpoS'-'lacZ (short) This study CL212 (PM1205) bolA'-'lacZ This study CL213 (PM1205) amiC'-'lacZ This study CL214 (PM1205) nlpD'-'lacZ This study CL215 (PM1205) zapB'-'lacZ This study CL216 (PM1205) rlpA'-'lacZ This study CL217 (PM1205) ftsA'-'lacZ This study Plasmid Description Source Chapter 3 pBRCS12 pBRPlac vector control [176] pBRPlac with sgrT coding sequence under pBRCV7 control of the Plac promoter [176] pBRCV7 with a 3xFLAG tag inserted at the pBRCS1 C-terminus of sgrT [164] pLCV1 with a point mutation that changes pLCV5 the fifth codon of sgrT to UAA [176] pHDB3 pBR322 derivative, vector control [170] pZA31R vector (NDEI and BAMHI) [106] pZACL1 ptsG wt (NDEI and BAMHI) This study
38 Table 2.1 (continued)
pZACL2 ptsG P384R This study pZACL3 ptsG V12F This study
PMdfA pT7-5/mdfA-His6 [107]
Ptet-vector P. Ragunathan
Ptet-dicF P. Ragunathan
Plac-vector Gottesman laboratory, NIH
Plac-dicF Gottesman laboratory, NIH
Plac-dicF3 [10]
Plac-dicF9 [10]
Plac-dicF21 [10] pNM12 [114] pBAD-ITSmetZ-metW [99] pBAD-ITSmetW-metV [99] pBAD-ITSZWmutGC [99] pBAD-ITSWVmutGC [99]
39 Table 2.2 Oligonucleotides used in this study
Oligos Description Chapter 3 O-CL056 5' CCCCCCCCCCcatatgATGTTTAAGAATGCATTTG 3' ptsG fwd O-CL057 5' CCCCCCggatccTTAGTGGTTACGGATGTAC 3' ptsG rev ptsG V12F O-CL183 5' GACAGAACGATGAAGCCGATCAGACCGTGCG 3' (D343G) ptsG V12F O-CL184 5' CGCACGGTCTGATCGGCTTCATCGTTCT 3' (D343G) rev ptsG P384R O-CL054 5' GGATCTGAAAACGAGGGGTCGTGAA 3' fwd ptsG P384R O-CL055 5' GTCGCGTCTTCACGACCCCTCGTTTT 3' rev ycfH::kn 5' linked ATGAATATTTTAGGTTTTTTCCAGCGGCTCGGTAGGGCGTTAC upstream O-CL167 CCTCATCTTTAAGAGAGACATC 3' ptsG EIIC 5' GGTTGAACATGCGGATAACCAAACTGAACACCACGAAGTAGG ycfH::kn EIIC O-CL168 CATCTTCAGTCGCGTCTTC 3' rev Chapter 4 5' GTTTGATCGCGCTAAATACTGTTCAGCACAAGGAATGCAAATG O-CL080 CCTGTGACGGAAGATCACTTCGC 3' tolC::cat fwd 5' GCCTTACGTTCAGACGGGGCCGAAGCCCCGTCGTCGTCATCAT O-CL081 TATCAATTCAGGCGTAGCAG 3' tolC::cat rev 5' CTCACCCAGCGGAAACCGCTCTACAGACGTTTAAATTTCTTAT O-CL082 GCCTGTGACGCAAGATCACTTCGC 3' yigL::cat fwd 5' GCGAAGTATCAGGTTGACAACTGACCAAATAAAGAACGATTA O-CL083 TTATCACTTATTCAGGCGTAGCAC 3' yigL::cat rev
Chapter 5 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATCTAT rplU'-'lacZ O-CL245 TGTGAATATTTATAGC 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACGCC rplU'-'lacZ O-CL246 AGTTGCGATGTCCAG 3' rev 5' ACCTGACGTTTTTATCGCAACTCTCTACTGTTTCTCCATGCCCT rplN'-'lacZ O-CL247 CGATATGGGGATTTT 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACACG rplN'-'lacZ O-CL248 GTGCGAGCCACCCAGAA 3' rev 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATGTTG ahpC'-'lacZ O-CL249 TTGCATTTGTAGGGC 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACTTC ahpC'-'lacZ O-CL250 GGTATCTTTTTCGGTGA 3' rev
40 Table 2.2 (continued)
5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATTTCG rpoS'-'lacZ O-CL251 GGTGAACAGAGTGCTA 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACTAA rpoS'-'lacZ O-CL252 GGCCTTTTCGTCAAAAA 3' rev (long) 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATAGCT ftsN'-'lacZ O-CL253 ATGCTGTTATTGCTTG 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACAGG O-CL254 CAGATTTCGTTGCTTTT3' ftsN'-'lacZ rev 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACTTC rpoS'-'lacZ O-CL255 CGCATCTTCATTTAAATC 3' rev (short) 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCTTTAAA bolA'-'lacZ O-CL256 TCAGTAAACTTCAT 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACATT bolA'-'lacZ O-CL257 GTGACGATAGCTTTCAT 3' rev 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATTTCG amiC'-'lacZ O-CL258 CAGGGTGCAAGTGTAA 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACCAG amiC'-'lacZ O-CL259 ACTGACCTGACTTACGC 3' rev 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATCTTTT nlpD'-'lacZ O-CL260 CCAGTGTTCAGTAGG 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACTGA nlpD'-'lacZ O-CL261 AGAAGTGTCAGAACAGCCTG 3' rev 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATGCCG zapB'-'lacZ O-CL262 CTGGACAGCGATGGCG 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACTTC zapB'-'lacZ O-CL263 GATTTCCATCTGCAACA 3' rev 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATAATG rlpA'-'lacZ O-CL264 TTGTCGAAAAGCGTGT 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTGTAAAACGACTACA rlpA'-'lacZ O-CL265 CTTACCGTCTGTTGCT 3' rev 5' ACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCATATAT ftsA'-'lacZ O-CL266 GGTAGACGCGGAAGGA 3' fwd 5' TAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACGTC O-CL267 GGGCAGAACTTCCCCTA 3' ftsA'-'lacZ rev
41 Chapter 3: The small protein SgrT controls transport activity of the glucose-specific phosphotransferase system2
3.1 Introduction
Uptake and metabolism of carbon sources is regulated by a variety of mechanisms to ensure a steady flow of intermediates through central metabolism. Under most circumstances, glucose is a preferred carbon source for Escherichia coli, yet under some conditions, metabolic flux becomes suboptimal and glucose transport and metabolism is disfavored [20, 152]. One condition of impaired glucose metabolism occurs when cells are exposed to non-metabolizable glucose analogs (e.g., α-methylglucoside) that are taken up and phosphorylated but cannot be metabolized further. This induces the so- called glucose-phosphate stress response, which allows cells to reduce sugar-phosphate accumulation and recover from stress. If the stress response is inactivated, cells show striking growth defects [90, 123, 165, 173] and in some cases even lysis [75, 151].
Growth of cells experiencing glucose-phosphate stress is improved by supplementation with glycolytic intermediates downstream of metabolic bottlenecks [151] or if sugar transport is inhibited [173, 175].
Glucose and the analog α-methylglucoside (αMG) are primarily transported into the cell through the major glucose transporter PtsG (EIICBGlc), while another analog, 2- deoxyglucose (2DG) is taken up mainly by the mannose transporter ManXYZ
(EIIABCDMan) [65]. PtsG and ManXYZ import and concomitantly phosphorylate incoming sugars via the phosphoenolpyruvate phosphotransferase system (PTS) comprised of several proteins that participate in a phosphorelay that begins with the
2 Chapter contains material from the following publication: Lloyd C.R., Park S., Fei J., Vanderpool C.K., J Bacteriol, 2017.
42 glycolytic intermediate phosphoenolpyruvate (PEP) as the phosphate donor [145]. The glucose PTS is especially significant since the EIIAGlc protein (that activates PtsG) has key regulatory roles in catabolite repression, which ensures preferential glucose utilization [59, 70, 74, 89].
Our studies characterizing the glucose-phosphate stress response have demonstrated that a small RNA, SgrS, whose synthesis is induced by glucose-phosphate stress, is the key regulatory effector of the response [173-175]. Like many other small
RNAs (sRNAs) in bacteria, SgrS carries out base pairing-dependent regulation of numerous mRNAs [16, 85, 133, 134, 150, 173]. Less typical is the second function of
SgrS, namely encoding the 43-amino acid protein SgrT [11, 175]. Unlike any other known dual-function sRNA-small protein pair, SgrS and SgrT act independently in the same pathway, albeit by different mechanisms [11, 175]. The base pairing activity of
SgrS ameliorates glucose-phosphate stress by inhibiting translation and promoting degradation of the ptsG and manXYZ mRNA transcripts thereby preventing synthesis of more sugar transporters during stress. In contrast, SgrT was shown to have no effect on sugar transporter mRNA levels, but could still reverse growth inhibition caused by stress
[11, 175]. These and other results suggested that SgrT acted by inhibiting glucose transporter activity [175]. SgrT and SgrS base pairing functions also act at different times during glucose-phosphate stress. The base pairing function acts immediately, whereas SgrT is not detected until ~30 minutes following the onset of stress [11]. The goal of the present study was to examine the target specificity and physiological roles of
SgrT in the glucose-phosphate stress response. We found that while the SgrS base pairing activity serves to inhibit further synthesis of both PtsG and ManXYZ, SgrT
43 specifically inhibits the transport activity of PtsG. Consistent with a mechanism of inhibition requiring physical interaction, SgrT localization to the membrane is PtsG- dependent. Amino acid residues in the N-terminal region of IIC (membrane) domain of
PtsG are required to confer sensitivity to SgrT-mediated inhibition of sugar transport activity. SgrT-mediated interference with the catabolite repression function of the glucose PTS allows utilization of alternative carbon sources, such as lactose, during glucose-phosphate stress. This provides a rationale for production of this small protein under glucose-phosphate stress conditions.
3.2 Results
3.2.1 Ectopic production of SgrT inhibits cell growth on minimal glucose medium
The base pairing activity of SgrS inhibits the synthesis of both the PtsG and
ManXYZ transport proteins by inhibiting translation of the corresponding mRNAs [15,
85, 150, 173]. Our hypothesis is that SgrT inhibits activity of sugar transport proteins. To test whether SgrT affects PtsG, ManXYZ or other sugar transporters, strains expressing sgrT from a plasmid were tested for growth on minimal media containing various carbon sources (Fig. 3.1). Growth of cells producing SgrT showed marked inhibition on glucose compared to cells carrying the vector control. In contrast, growth on all other carbon sources tested appeared similar between vector control and sgrT-expressing cells (Fig.
3.1). Notably, growth on mannose was unaffected by SgrT, and as ManXYZ is the only mannose transporter, these results suggest that SgrT affects only glucose transporters.
Interestingly, the trehalose transporter TreB (EIIBCTre) does not have a cognate EIIA and instead relies on EIIAGlc for activation. If SgrT affected glucose transport by interfering with EIIAGlc activity, we would expect sgrT-expressing cells to demonstrate a growth
44 defect on trehalose. Since cells expressing SgrT grow uninhibited on trehalose, we postulate that SgrT does not act at the level of EIIAGlc to inhibit glucose transport.
3.2.2 SgrT inhibits PtsG but not ManXYZ
Results of growth experiments suggested that SgrT preferentially affects PtsG but not ManXYZ and our previous work implicates sugar transport as the most likely step
affected by SgrT [175]. To further test this, we utilized a transcriptional PsgrS-lacZ fusion to monitor induction of the glucose-phosphate stress response upon exposure of cells to
αMG or 2-deoxyglucose (2DG). These two glucose analogs are transported by different
PTS proteins; αMG is primarily transported via PtsG (EIICBGlc) [65, 150, 163] whereas
2DG is mainly transported by ManXYZ (EIIABCDMan) [148]. We therefore utilized these molecules to probe the activity of SgrT on these two sugar transporters. When cells were
exposed to αMG, β-galactosidase activity of the PsgrS-lacZ strain carrying the vector control was high (Fig. 3.2A), consistent with uptake of αMG and induction of the glucose-phosphate stress response. In cells expressing SgrT, β-galactosidase activity was reduced by ~10-fold compared with vector control cells (Fig. 3.2A), supporting the idea that SgrT inhibits uptake of αMG. We noted that SgrT-expressing cells exposed to
αMG still had higher levels of β-galactosidase activity than untreated cells, and hypothesized that ManXYZ might be responsible for a low-level of αMG uptake that was insensitive to SgrT. To test this hypothesis, we repeated the experiments in a manXYZ mutant strain. Compared with the parent strain, the manXYZ mutant showed lower levels
of induction of PsgrS-lacZ when exposed to αMG and induction was completely lost when
SgrT was produced (Fig. 3.2A). These data suggest that both PtsG and ManXYZ contribute to uptake of αMG and that SgrT only inhibits the activity of PtsG. To further
45 test whether SgrT could affect transport through ManXYZ, we measured induction of
PsgrS-lacZ in response to the ManXYZ-specific substrate 2DG [65]. We note that 2DG is a less potent inducer of PsgrS-lacZ compared with αMG (note the difference in scales between Fig. 3.2A and 3.2B). Nonetheless, 2DG promoted a >10-fold induction of PsgrS- lacZ in vector control cells, and a similarly large induction in SgrT-producing cells (Fig.
3.2B). Together, these data strongly suggest that SgrT specifically affects the transport activity of PtsG but not ManXYZ.
3.2.3 SgrT localizes to the membrane in a PtsG-dependent manner
Because SgrT was found to specifically affect uptake of (Fig. 3.2) and growth on
(Fig. 3.1) substrates of PtsG, we hypothesized that SgrT would interact with PtsG and localize to the cell membrane. In wild-type (WT) or ptsG cells, previously characterized and functional SgrT-3 FLAG proteins [175]were labeled by immunofluorescent staining using an anti-FLAG antibody followed by Alexa Fluor 647-labeled secondary antibody and imaged using superresolved single-fluorophore microscopy [72] (Fig. 3.3). Two- dimensional (2D) projections in the xy plane from a 3D reconstructed image within different z depths are shown in Fig. 3.3A (1,000 nm) and B (200 nm). Images of individual cells were aligned and projected along the cell’s longitudinal axis to the cell cross section (Fig. 3.3C) to generate heat maps of SgrT distribution, which demonstrates membrane versus cytoplasmic localization of SgrT (Fig. 3.3D). The intensity of the SgrT-
3 FLAG signal is plotted as a function of cell radius (R, where the center of the cell is at
0) (Fig. 3.3E). In WT cells producing PtsG, SgrT preferentially localized to the cell periphery, indicated by a higher probability of SgrT localization at larger R values in WT cells than in ptsG cells (Fig. 3.3D and E). We note that the observed radial distribution of
46 SgrT in WT cells peaks at 200 nm, which is smaller than expected for a live E. coli cell with an average diameter of 1 μm. We think two main factors account for this difference.
First, we overexpressed SgrT for this imaging experiment, so the cytoplasmic portion of
SgrT in excess of what could be bound by PtsG would be expected to shift the histogram toward a lower R value. Additionally, treatment required for the imaging protocol alters cell shape and con-tributes to a reduction in cell radius. Nevertheless, it is very apparent that deletion of ptsG shifted localization of SgrT away from the periphery (membrane region, higher R values) toward the cytoplasm (lower R values) (Fig. 3.3D and E). These data are consistent with the model that SgrT localizes to the membrane in a PtsG- dependent manner.
3.2.4 The EIIC domain of PtsG is required for full sensitivity to SgrT
Once we established that SgrT inhibits PtsG specifically and its localization to the membrane is dependent on PtsG, we took a genetic approach to assess which region of
PtsG makes it susceptible to inhibition by SgrT. PtsG is comprised of three main functional domains: the membrane-bound IICGlc domain, the linker region, and the soluble IIBGlc domain. A previous study demonstrated that the IICGlc domain of PtsG most likely confers sub-strate specificity for glucose. In that study, a chimeric transporter composed of the PtsG IICGlc domain and the NagE IIBGlcNAc domain (for N- acetylglucosamine transport) was constructed (EIICGlcIIBGlcNAc), and its substrate specificity was assessed [73]. The fusion junction was the LKTPGRED motif, which is located in the linker and is identical in PtsG and NagE. It was shown previously that the chimeric EIICGlcIIBGlcNAc (PtsG-NagE) protein could phosphorylate glucose but not
GlcNAc, suggesting that the IIC domain dictates the specificity of PtsG for glucose [73].
47 Since our results show that SgrT inhibits growth on glucose but not GlcNAc (Fig. 3.1), we predicted that SgrT would inhibit growth on glucose of cells expressing the
EIICGlcIIBGlcNAc (PtsG-NagE) (Fig. 3.4A) chimeric protein by targeting the IICGlc domain, which dictates glucose specificity. Using cells producing only one of the transporters chimeric PtsG-NagE (EIICGlcIIBGlcNAc), wild-type PtsG (EIICBGlc), or wild-type NagE
(EIICBAGlcNAc), we tested for SgrT-dependent inhibition of growth on glucose minimal medium (Fig. 3.4B). As expected, cells producing wild-type PtsG grew well in this medium in the absence of SgrT (Fig. 3.4B, orange line), but when SgrT was produced, these cells were strongly inhibited (Fig. 3.4B, light blue line). PtsG-NagE cells also grew in glucose minimal medium (Fig. 3.4B, purple line), consistent with previous data indicating that the IIC domain of PtsG is a primary determinant of glucose specificity.
When SgrT was produced in the PtsG-NagE strain, growth was strongly inhibited for 16 h, but then cells resumed growth (Fig. 3.4B, green line). This phenotype and the timing of resumed growth were consistent for many biological replicates. Cells producing NagE were unable to grow on minimal glucose medium regardless of whether SgrT was produced (Fig. 3.4B, red and blue lines). Strong growth inhibition of the strain producing the chimeric protein (with only EIIC from PtsG) by SgrT suggests that the key determinants defining SgrT specificity for PtsG reside in the IIC domain. However, the fact that PtsG-NagE cells can escape SgrT-mediated inhibition after prolonged incubation implies that sequences in the IIB domain of PtsG (absent from the chimeric transporter) may also contribute in some way to the PtsG-SgrT interaction.
48 When cells were grown in GlcNAc, the PtsG strain grew similarly to the NagE strain
(Fig. 3.4C, orange and red lines). The robust growth provided by PtsG on GlcNAc is somewhat surprising given that it has been reported that NagE and ManXYZ transport this substrate [80, 145]. Interestingly, a mutation in the IIC domain of PtsG has been reported to allow the use of glucosamine by altering its regulation [144]. Perhaps in our strain background, where manXYZ and nagE are deleted, regulation of ptsG is altered in a way that allows GlcNAc utilization. Regardless, we note that SgrT strongly inhibited
PtsG-mediated growth on GlcNAc (Fig. 3.4C, light blue line). This suggests that SgrT can inhibit PtsG activity independent of the transported substrate. Given that both PtsG and NagE promote growth on GlcNAc, it was not surprising to find that chimeric PtsG-
NagE also provides for robust growth on this sugar (Fig. 3.4C, purple line). Interestingly, we found that SgrT could also transiently inhibit growth of both NagE and PtsG-NagE cells on GlcNAc minimal medium (Fig. 3.4C, blue and green lines). (Note that this transient phenotype is not apparent on plates in Fig. 3.1 as transient growth inhibition on
GlcNAc has already resolved by 24 h.) This result suggests that NagE and PtsG-NagE share determinants conferring partial susceptibility to SgrT. These could be localized to the linker region or other regions of similarity between the PtsG and NagE IIC domains
(Fig. 3.5).
3.2.5 PtsG(V12F) but not PtsG(P384R) is resistant to SgrT-mediated transport inhibition
To further define the interactions between the IIC domain of PtsG and SgrT, we tested susceptibility of various ptsG mutants to SgrT-mediated inhibition of αMG
transport as described above, using the PsgrS-lacZ reporter fusion. We began by testing
49 mutants reported to have either increased transport of glucose or αMG, or broadened substrate specificities [42, 129]. The residues in these mutants reside in the cytoplasmic portion of PtsG. Most of these mutants (S157E, H339Y, K257N, M17T, D343G) were still inhibited by SgrT. The Jahreis reported that a PtsG mutant with broadened substrate specificity PtsG(P384R), was not sensitive to inhibition by SgrT [96]. We constructed this same mutant and found that the strain producing PtsG(P384R) was substantially less
responsive to induction of PsgrS-lacZ by αMG compared to the strain producing wild-type
PtsG (Fig. 3.5A). This suggests that this mutation impairs the function of PtsG and reduces transport of αMG. In contrast with the findings of Jahreis and colleagues [52], we found evidence that PtsG(P384R) activity could still be inhibited by SgrT (Fig. 3.5A).
When SgrT was produced in the PtsG(P384R) strain, the fold reduction in PsgrS-lacZ activity was comparable to that observed in the wild-type PtsG strain. Thus, our data do not support the idea that SgrT requires this proline residue (P384) in the PtsG linker region in order to control PtsG activity. Further evidence arguing against this portion of the PtsG linker as a determinant of SgrT susceptibility is the conservation of the proline and surrounding residues within the linker between PtsG and NagE; the LKTPGRED motif is identical in both proteins. If this motif were sufficient to confer susceptibility to
SgrT, we would expect ectopic production of SgrT to inhibit NagE activity and growth on N-acetylglucosamine. Instead, SgrT does not strongly inhibit growth on GlcNAc
(Figs. 3.1, 3.4C). Residues at the N-terminus of PtsG (within the IIC domain) have previously been implicated in modulating the rate of glucose (and αMG) transport [1,
22]. We tested the activity and SgrT-sensitivity of another PtsG mutant, PtsG(V12F), which was previously shown to have an enhanced rate of αMG transport [1, 129]. This
50 mutant was also tested by Jahreis and coworkers for interaction with SgrT by co- immunoprecipitation, and their results suggested that PtsG(V12F) and SgrT could still interact [96]. However, given the discordance of our results for the P384R mutation, we proceeded to test the V12F mutant as described above. In the absence of stress, cells with
wild-type and V12F PtsG had similar levels of PsgrS-lacZ activity (Fig. 3.5B). As expected, when wild-type cells were stressed, PsgrS-lacZ activity increased substantially
(Fig. 3.5B, compare activity in wt/vector cells –αMG versus +αMG). Ectopic production of SgrT reduced this activity (Fig. 3.5B), consistent with SgrT-mediated inhibition of
wild-type PtsG activity. In the PtsG(V12F) strain, exposure to αMG also induced PsgrS- lacZ activity (Fig. 3.5B, compare activity in V12F/vector cells without αMG versus those with αMG), but production of SgrT had no effect on this activity. These observations suggest that the transport activity of PtsG(V12F) is similar to wild-type PtsG but that this mutation renders PtsG(V12F) insensitive to inhibition by SgrT.
3.2.6 SgrT strongly inhibits preexisting PtsG transporters
Our previous work indicates that mechanistically, the base pairing activity of SgrS only stops new synthesis of PtsG transporters but has no effect on pre-existing transporters [134, 175]. In contrast, we hypothesize that SgrT has an immediate inhibitory effect on PtsG activity. To test the relative effects of SgrT and SgrS base pairing on PtsG transport activity, we directly measured the uptake of [14C]αMG by
ΔsgrS cells carrying a vector control or ectopically expressing sgrT alone or an sgrS allele possessing only the base pairing region for 20 minutes prior to exposure of cells to
[14C]αMG. Cells carrying the vector control accumulated [14C]αMG, as evidenced by the increase in cell-associated radioactivity over time (Fig. 6). The negative control, a ptsG
51 mutant, failed to accumulate appreciable levels of [14C]αMG. Cells producing SgrT were similar to the ptsG mutant and showed very little uptake of [14C]αMG (Fig. 6). In contrast, cells expressing the base pairing-only SgrS looked very similar to the positive- control cells, and accumulated [14C]αMG at a similar rate (Fig. 6). These results support our overall model in which the base pairing activity of SgrS acts only to inhibit new PtsG synthesis, but that the preexisting PtsG (which is extremely stable [134]) remains active and SgrT is required to inhibit this activity.
3.2.7 SgrT-mediated inhibition of PtsG prevents inducer exclusion, promoting growth by allowing utilization of alternative carbon sources
Inducer exclusion represents one of the mechanisms that ensures preferential utilization of glucose by enteric bacteria when glucose is present in a mixture with other carbon sources [34]. Inducer exclusion requires the dephosphorylated form of EIIAGlc, which accumulates when cells are actively importing glucose via PtsG. Under these conditions, EIIAGlc interacts with a variety of transport proteins and enzymes to inhibit uptake or utilization of alternative carbon sources [34]. In a previous study, we demonstrated robust inducer exclusion when cells were grown in the presence of glucose and lactose, evidenced by very low expression of the lac genes, when SgrT was not produced. In contrast, in cells making SgrT, inducer exclusion was relieved and lac genes were highly expressed [175]. These data are consistent with the model that SgrT- mediated inhibition of PtsG activity results in accumulation of phospho-EIIAGlc, relieving inducer exclusion and promoting lac expression. Based on these previous results, we hypothesize that SgrT-mediated relief of inducer exclusion may allow cells experiencing glucose-phosphate stress to utilize alternative carbon sources [153]. To test
52 this, ΔsgrS cells expressing a vector control or SgrT were grown in the presence of αMG with or without lactose and simultaneously monitored for growth and lac expression (Fig.
3.7). Without lactose, cells expressing SgrT showed growth improvement when compared to vector control and reached a density of 1.0 after 400 min (Fig. 3.7A). In the presence of lactose, however, SgrT-expressing cells reached the same density in only 200 min and ultimately grew to a higher density. Vector control cell growth was also improved by lactose, but only after a prolonged lag phase (Fig. 3.7B). SgrT-producing cells also showed 2-fold increased endogenous β-galactosidase activity compared with control cells at early time points after stress induction (data not shown), consistent with relief of inducer exclusion in these cells. These data demonstrate that SgrT production not only aids cells in overcoming the stress of accumulating sugar phosphates but also promotes utilization of alternative carbon sources, thereby markedly improving stress recovery and growth.
3.3 Discussion
SgrS is a versatile sRNA able to produce a functional protein and regulate many targets to alleviate glucose-phosphate stress [15]. Among these targets, PtsG and
ManXYZ transporters are particularly important, as they are directly responsible for importing stress-inducing molecules [88, 142]. SgrT and SgrS base pairing act independently to tackle the problem of sugar transport under stress conditions from two directions. The SgrS base pairing function is critical and is used first to inhibit further synthesis of sugar transporters [11], after which SgrT is produced to inhibit existing PtsG transporters [11]. In this study, we determined that SgrT specifically affects activity of only one sugar transporter, namely PtsG (EIICBGlc) (Figs. 1, 2, 4). This stands in contrast
53 with the base pairing activity of SgrS, which impacts synthesis of both PtsG [85, 173] and another sugar transporter, ManXYZ [150]. We discovered that the IIC domain of
PtsG contains determinants that make PtsG but not a highly similar transporter, NagE, susceptible to inhibition by SgrT (Fig. 3.4). Preferential localization of SgrT to cell membrane regions in ptsG+ but not ΔptsG strains (Fig. 3) suggests that SgrT modulates
PtsG activity via physical interactions. Finally, we demonstrated that SgrT-producing cells have a growth advantage during glucose-phosphate stress, particularly when an alternative carbon source is provided (Fig. 3.7). Cumulatively, our work upholds our model that the protein (SgrT) component of the dual-function sRNA SgrS provides a specific mechanism for inhibiting sugar transport activity and promoting cell growth under glucose-phosphate stress conditions (Fig. 3.8).
Under stress, SgrS base pairing activity inhibits the synthesis of both the PtsG and
ManXYZ transporters responsible for importing αMG and 2DG. In contrast, SgrT solely targets PtsG and has no effect on 2DG transport (Fig. 3.2). Why might SgrT differentiate between these transporters, and what does this tell us about the nature of glucose- phosphate stress? Unlike ManXYZ, the proteins comprising the glucose PTS are critical for metabolic regulation via carbon catabolite repression (CCR). During glucose transport, EIIAGlc (Crr) exists largely in a dephosphorylated state due to rapid phosphate transfer to PtsG. Dephosphorylated EIIAGlc binds and inhibits other transporters, such as
LacY, causing inducer exclusion (Fig. 3.8 and [34]). Another effect of low phospho-
EIIAGlc levels is reduced production of the small molecule cyclic AMP (cAMP), since only phospho-EIIAGlc binds to and activates the adenylate cyclase to stimulate cAMP production [48, 62, 135]. These two outcomes of CCR, inducer exclusion and reduced
54 cAMP production, together reduce the activity and synthesis, respectively, of transporters for alternative carbon sources, thus favoring glucose utilization. The glucose analog
αMG also stimulates CCR, which not only favors further transport of αMG, but also prevents uptake and metabolism of other carbon sources. The stress response enacted by
SgrS and SgrT counteracts the CCR response, and in this study we show that this allows the utilization of metabolizable sugars such as lactose, which helps cells thrive during stress (Fig. 3.8).
The use of alternative non-PTS carbon sources may be especially beneficial for glucose-phosphate stress recovery since the PTS-dependent transport of αMG depletes
PEP, which subsequently cannot be replenished by metabolism. In fact, the depletion of such critical metabolic intermediates is thought to be the cause of stress as opposed to any inherent toxicity associated with sugar phosphate accumulation, as the addition of sugar phosphates downstream of the metabolic block allows cells to recover even while
αMG is actively transported [151]. Although the exact cause of stress in natural environments is still unknown, it is clear that conditions resulting in accumulation of non- metabolizable phosphorylated intermediates (or their analogs) of the early steps of glycolysis promote rapid induction of the stress response. There is evidence that αMG and 2DG exist in nature. Klebsiella pneumoniae can metabolize αMG as a carbon source
[139], and αMG has been found in environmental water samples [140]. Saccharomyces cerevisiae can detoxify 2DG [147]. Gammaproteobacteria, mainly enteric bacteria, are the only organisms known to possess this particular stress response [71, 136]. Whether these sugar analogs or similar compounds are present in the gut or other environmental niches where these organisms reside is undetermined.
55 It is worth noting that our experiments demonstrated a clear role for the IIC domain of PtsG in conferring susceptibility to SgrT, whereas others [52, 96] have suggested that the linker region connecting IIC and IIB domains is involved in SgrT binding. Bimolecular fluorescence complementation experiments performed by the
Jahreis group [96] tested the interactions between SgrT and various lengths of PtsG by fusing them to different domains of green fluorescent protein (GFP) and monitoring GFP complementation by fluorescence. They showed that complementation occurred most strongly when both the IIC domain and linker were present but found no interaction between SgrT and the IIC domain alone [96]. We note that these experiments utilized protein fusions between PtsG fragments or SgrT and different domains of GFP. Our experience with SgrT protein fusions has been that any but small epitopes strongly impair
SgrT function and prevent it from controlling PtsG (C. R. Lloyd and C. K. Vanderpool, unpublished data). Thus, it is possible that bimolecular fluorescence complementation assays with protein fusions did not fully capture relevant SgrT-PtsG interactions. These results, along with those we present here, suggest that determinants in both the linker and
IIC domain are important for SgrT interaction. Interestingly, in a crosslinking and copurification experiment (using SgrT tagged with the small hemagglutinin [HA] epitope), Kosfeld and Jahreis found evidence that SgrT preferentially interacts with dephosphorylated PtsG [96], which would be the predominant form present during active glucose transport as the phosphate is rapidly transferred to the incoming sugar. This observation suggests that SgrT might only associate with PtsG during active transport.
We envision a model where SgrT interacts with PtsG and blocks sugar passage directly or causes a conformational change that prevents phosphorylation of PtsG. This would leave
56 the EIIAGlc protein in a phosphorylated state – unable to bind and inhibit the lactose permease and other carbon utilization proteins, thereby enabling use of any other available carbon sources (Fig. 3.8). More structure-function studies are necessary to determine if the interaction between SgrT and EIICBGlc is direct or requires an intermediate, and to elucidate the molecular mechanism of SgrT activity.
57 3.4 Figures
Figure 3.1 Ectopic production of SgrT inhibits cell growth on minimal glucose medium. ΔsgrS::kan, lacIq+ cells (CV104) carrying a vector control (pBRCS12, left) or + Plac-sgrT plasmid (pBRCV7, right) were grown on minimal media with ampicillin, IPTG, and one of the following carbon sources at 0.2% (from top) glucose, mannose, N- acetyl glucosamine (GlcNAc), fructose, and trehalose.
58
Figure 3.2 SgrT inhibits PtsG transport activity, but not ManXYZ activity. Three biological replicates of strain CL104 (Δlac, mal::lacIq+, sgrS::tet) or CL105 (Δlac, q+ mal::lacI , sgrS::tet, manXYZ::kan) containing a PsgrS-lacZ fusion and harboring either + vector control (pBRCS12) or Plac-sgrT (pBRCS1) plasmids were tested for the response to αMG (A) or 2DG (B) as detected by induction of the sgrS promoter. Cells were grown in TB overnight, then subcultured 1:200 and grown to an OD600 of 0.1. IPTG (0.1 mM) was added and then cultures were split, with half receiving 0.1% 2DG or 0.5% αMG and the other half receiving an equivalent volume of ddH2O. Samples were taken after 120 minutes and β-galactosidase activity measured.
59
Figure 3.3 SgrT localizes to the cell membrane in a PtsG-dependent manner. Images in A and B are from super-resolution microscopy and detection of SgrT-3XFLAG by immunofluorescence. A) The 2D projection images on XY plane for ΔptsG cells (left) and WT cells (right) for the entire Z range of 1000nm. (B) The 2D projection images on XY plane for ΔptsG cells (left) and WT cells (right) for the middle Z plane (200 nm range). (C) 20% of each end of poles or septum was cut for 2D projection analysis. (D) The 2D projection images on XZ plane for 76 ΔptsG cells (left) and 71 WT cells (right) with the color scale bar. Each pixel is 30 x 30 nm2, and the total number of spots were counted and plotted as heat-maps. Cells are combined from two independent experiments. (E) The probability density of finding a spot at R distance from the length axis of cells was plotted by 40 nm binning, with renormalization of keeping the peak value of each case as 1.
60
Figure 3.4 Strong SgrT-mediated growth inhibition requires the IIC domain of PtsG. (A) Schematic depicting the EIICGlcBNag chimera. The PtsG IIC domain is fused to the NagE IIB domain at their identical linker motif (LKTPGRED). (B) Cultures of CL174 (Δlac, mal::lacIq+, sgrS::tet, manXYZ::cat, ΔptsG, ΔgalP, EIICBANag (NagE+)), CL175 (Δlac, mal::lacIq+, sgrS::tet, manXYZ::cat, ΔgalP, EIICGlcEIIBNag+)), and CL188 (Δlac, mal::lacIq+, sgrS::tet, manXYZ::cat, nagE::kan, ΔgalP, EIICBGlc (PtsG+), harboring + either vector control (pBRCS12) or Plac-sgrT (pBRCS1) plasmids were cultured in M63 glucose media plus 1 mM IPTG to induce SgrT and monitored for growth inhibition in biological triplicates using a 96-well plate reader. (C) Cultures the strains used in (B) were grown in M63 GlcNAc media with 1 mM IPTG to induce SgrT and monitored for growth over time using a 96-well plate reader. Data are the mean of three biological replicates.
61
Figure 3.5 Identification of PtsG residues conferring resistance to SgrT-mediated q+ transport inhibition. (A) CL108 cells (Δlac, mal::lacI , PsgrS-lacZ (short), sgrS::tet, ptsG::kan) harboring plasmids containing wild-type ptsG (pZACL1), ptsG P384R + (pZACL2) as well as vector control (pBRCS12) or Plac-sgrT (pBRCV7) were grown in TB overnight and subcultured 1:100 in TB plus 1 mM IPTG and 50ng aTc and grown to an OD600 of 0.5. Cultures were then split and half received treatment with 0.05% αMG and β-galactoside activity measured after 45 minutes. (B) The same procedure was repeated using the ptsG V12F mutation (pZACL3).
62
Figure 3.6 SgrT strongly and immediately inhibits transport activity of PtsG. CL113 cells (Δlac, mal::lacIq+, galP::kan, sgrS::tet, manXYZ::cat) carrying vector control + (pBRCS12), Plac-sgrT (pBRCS1), or sgrS base pairing-only (pLCV5) plasmids were grown in M63 glycerol medium with 0.1 mM IPTG, then washed with M63 salts. Cells were exposed to 14C-αMG, and monitored for accumulation of radioactivity over time. The results shown are the average of biological triplicates.
63
Figure 3.7 SgrT facilitates use of alternative carbon sources during stress. CS136 + cells (MG1655, ΔsgrS::kan) carrying vector control (pHDB3) or Plac-sgrT (pBRCV7) plasmids were grown in TB medium with 0.5% αMG plus 1.0 mM IPTG without (A) or with lactose (B) and growth measured by recording optical density at 600 nm over time.
64
Figure 3.8 Model for regulation of PtsG activity by SgrT. During active αMG transport (left), PtsG and EIIAGlc are dephosphorylated because phosphate is rapidly transferred to the incoming sugar. EIIAGlc binds the lactose permease protein (among others), inhibiting its activity and enacting inducer exclusion. SgrT binding to PtsG (right) inhibits transport, stopping the flow of phosphate so that phosphorylated EIIAGlc accumulates. P-EIIAGlc no longer inhibits transport or utilization of alternative carbon sources, thus inducer exclusion is relieved [175]. This allows utilization of other carbon sources, e.g., lactose, leading to promotion of growth.
65 Chapter 4: The impact of glucose-6-phosphate and tolC mutants on glucose- phosphate stress3
4.1 Introduction
Glucose has long been recognized as the preferred carbon source for E. coli since its use actively prevents that of other carbon sources by way of carbon catabolite repression (CCR) [113]. While glucose supports fast growth in E. coli, non- metabolizable glucose analogs, such as α-methyl glucoside (αMG) inhibit growth altogether in a phenomenon known as glucose-phosphate stress. Both glucose and αMG enter the cell primarily through the phosphoenolpyruvate (PEP) phosphotransferase system (PTS) transporters EIICBGlc (the major glucose transporter encoded by ptsG)- and
EIIABCDMan (the major mannose transporter encoded by manXYZ). PTS transporters utilize the glycolytic intermediate PEP as a phosphate donor to phosphorylate and prime incoming sugars for metabolism via a phosphotransfer cascade comprising several sugar- specific and nonspecific proteins. During active glucose transport, one of the proteins in the glucose-specific phosphorelay, EIIAGlc, not only passes phosphate directly to EIICBGlc for simultaneous sugar transport and phosphorylation, but also participates in CCR by binding and inhibiting other sugar permeases [34]. Transport of glucose generates glucose-6-phosphate that can proceed through glycolysis to replenish PEP and other important metabolic intermediates en route to ATP production. However, αMG transport accumulates non-metabolizable αMG-6-phosphate, which is bacteriostatic. While αMG-
6-phosphate accumulation is deleterious by some unknown mechanism, it is not thought
3 This chapter contains material from the following publication: Richards, G.R., et al., Depletion of glycolytic intermediates plays a key role in glucose-phosphate stress in Escherichia coli. J Bacteriol, 2013. 195(21): p. 4816-25.
66 that sugar phosphates themselves cause glucose-phosphate stress as cells exposed to
αMG can recover when supplemented with glucose-6-phosphate, fructose-6-phosphate, or fructose-1,6-bisphosphate [151]. The work described in this chapter demonstrates that this rescue effect is not due to decreased uptake of αMG.
While supplying cells with glycolytic intermediates downstream of an αMG-6-P- induced blockage can rescue growth inhibition, the members of a designated glucose- phosphate stress response can also recover growth: these are the transcriptional regulator
SgrR, the small RNA (sRNA) SgrS, and its cognate small protein SgrT. SgrR detects stress via an unknown mechanism and activates transcription of sgrS [173, 174]. SgrS prevents further transport of αMG by posttranscriptionally inhibiting the synthesis of
EIICBGlc and EIIABCDMan transporters [150]. Additionally, SgrS acts as an mRNA from which SgrT is translated [175, 176]. SgrT also prevents further influx of αMG by directly inhibiting preexisting EIICBGlc transport activity and, as a result, overrides CCR allowing less favorable carbon sources to be utilized for growth recovery [11, 111].
There are established mechanisms for the cell to prevent further influx of sugar phosphates, but what becomes of the accumulated αMG-6-P that initiated stress? It has been suggested that these sugar phosphates undergo dephosphorylation and subsequent efflux, since the charged phosphate group retains sugars within the cell [51, 68, 183].
The finding that the phosphatase YigL dephosphorylates αMG-6-P and that yigL mutants retain more αMG than wild type cells supports this [134]. Interestingly, the YigL mRNA is stabilized by SgrS, further demonstrating its role in the glucose-phosphate stress response [134]. While the phosphatase has been identified, the efflux pump through which αMG is flushed out of the cell remains to be determined. SetA was an excellent
67 candidate since it is cotranscribed with sgrST under glucose-phosphate stress, however radiolabled αMG efflux assays demonstrated it is not the pump responsible for αMG efflux [164]. The study described in this chapter suggests that the multidrug efflux pump
TolC may be involved.
TolC is an outer membrane channel that interacts with various other inner membrane transporters, such as AcrAB, to efflux a variety of substrates from xenobiotics to metabolites [188]. It is the extrusion of toxic metabolites that makes TolC an appealing candidate for αMG export. It should be noted that because of the promiscuity of the protein, tolC mutants exhibit pleiotropic effects on cell physiology [171].
Nevertheless, previous studies of tolC mutants have illuminated the potential roles of efflux in maintaining homeostasis under stress. tolC mutants have difficulty growing in minimal glucose medium [35], are more sensitive to antibiotics and toxins [171], accumulate toxic L-cysteine [184] and cAMP [61], and exhibit upregulation of the transcription factors marA, soxS, and Rob [154], which collectively suggests that TolC exports a variety of toxic metabolites. This study demonstrates through growth, efflux, and transcriptional fusion reporter assays that tolC make sgrS mutants more sensitive to
αMG.
4.2 Results
4.2.1 Glucose-6-phosphate rescues glucose-phosphate stress but does not affect cellular αMG transport
αMG6P accumulation occurs because it cannot be converted into fructose-6- phosphate by phosphoglucose isomerase causing a blockage in glycolysis. Work by our lab has established however, that supplying cells with glycolytic intermediates at or
68 downstream of this blockage rescues cell growth under glucose-phosphate stress.
Glucose-6-phosphate is one such intermediate capable of rescuing cell growth [151].
While we hypothesize that this rescue effect is due to repletion of glycolytic intermediates necessary for growth that would otherwise be depleted during stress, we wanted to test whether rescue was also due in part to glucose-6-phosphate interfering with αMG transport. αMG is transported primarily through EIICBGlc [65], glucose-6- phosphate (and fructose-6-phosphate) are transported through the phosphate and hexose-
6-phosphate antiporter UhpT [83, 161, 182], so direct competition for transport is unexpected. However, we tested the uptake of [14C] αMG over time by both wild type and sgrS mutants in the presence and absence of G6P (Fig. 4.1). We found that G6P had no effect on αMG transport. This, combined with other findings from our group that
G6P rescues cell growth when combined with αMG, suggests that sugar phosphates are not inherently toxic and that instead, metabolic obstruction is responsible for glucose- phosphate stress [151].
4.2.2 Mutating the multidrug efflux pump tolC in an sgrS background further diminishes cell growth under glucose-phosphate stress
Although sugar phosphates per se are not toxic to the cell, it is clear that their accumulation during impaired glycolysis inhibits growth [90, 139]. While we understand the mechanisms cells use to inhibit further influx of these sugars by affecting transport proteins, we do not understand what becomes of the phosphosugars that initiated stress.
One possible fate is efflux from the cell. TolC is a multidrug efflux pump that has been implicated in removing a variety toxic accumulated metabolites from the cell and was therefore a good candidate for the removal of accumulated αMG [64, 188]. We first
69 tested the growth of a tolC mutant on LB with αMG and did not see a growth defect (Fig.
4.2). However, an sgrS tolC double mutant was more growth defective than an sgrS mutant (Fig. 4.2) suggesting that loss of tolC exacerbates stress.
For metabolites such as phosphosugars to be effluxed, they must first be dephosphorylated. The phosphatase responsible for dephosphorylating αMG6P is YigL, which is a member of the SgrS regulon [134]. While a yigL mutant growth is not impaired growing on LB with αMG (as it is in minimal glycerol medium), sgrS yigL double mutants are inhibited and resemble an sgrS mutant phenotype on LB with αMG
(Fig. 4.2). Interestingly, an sgrS tolC double mutant suffers more growth inhibition than either an sgrS or sgrS yigL mutant (Fig. 4.2). This growth inhibition can also be observed in an sgrS yigL tolC triple mutant (Fig. 4.3) suggesting TolC may play a role in glucose- phosphate stress recovery.
4.2.3 tolC mutants experience higher induction of the glucose-phosphate stress response
Because tolC mutants exacerbate growth defects in an sgrS mutant background, we asked whether this mutation affected induction of the stress response by measuring
the activity a transcriptional sgrS reporter fusion (PsgrS-lacZ). While lone tolC mutants do not exhibit growth defects under glucose-phosphate stress, they do activate transcription of the stress response to a comparable level of an sgrS mutant (Fig. 4.4), whereas yigL mutants experience lower induction of sgrS. Interestingly, yigL tolC double mutants and sgrS yigL tolC triple mutants experience similar levels of stress induction as a yigL mutant (Fig. 4.4). These results are contrary to the observed growth phenotypes in which the triple mutant is the most growth inhibited. The interpretation of these data is
70 complicated by the fact that we don’t know what signal induces the stress response. TolC is responsible for eliminating a number of molecules from the cell; perhaps one of these substrates can induce the stress response independently of αMG.
4.2.4 tolC mutants exhibit impaired αMG efflux
To more directly test whether TolC plays a role in αMG efflux, we conducted an efflux assay in which the retention of radiolabled [14C] αMG was measured over time in wild type cells versus sgrS, tolC, yigL, and tolC yigL mutants (Fig. 4.5). While these are preliminary data representative of a single trial, we find that over time tolC mutants retain approximately two-fold more αMG than wild type cells (Fig. 4.5 second columns versus first). Interestingly, while yigL mutants have been previously shown to be efflux defective, in this experiment they were comparable to wild type. However, yigL mutants are compromised when combined with tolC mutants (Fig. 4.5); the tolC yigL double mutant retains a 5-fold excess of αMG compared to wild type further supporting the observation that dephosphorylation is required for efficient efflux [133].
4.3 Discussion
The precise nature of glucose-phosphate stress, why it is toxic, and how it is sensed by cells remains uncertain. However, while it has long been thought that sugar phosphates themselves are toxic, this and other work by our group demonstrates that it is not accumulation of sugar phosphates per se that is responsible for glucose-phosphate stress, as addition of glucose-6-phosphate and fructose-6-phosphate both rescue cell growth [151] even while αMG accumulates – since competition for transport between
G6P and αMG is unaffected by supplementing cells with G6P (Fig. 4.1). These data suggest that it is the interruption of glycolysis that is deleterious. This agrees with
71 previous observations that mutations in the glycolytic enzymes pgi and pfkA also produce glucose-phosphate stress [90, 123]. We hypothesize that because the cell uses the glycolytic intermediate PEP to generate αMG6P, but cannot replenish PEP levels by metabolizing αMG6P, the PEP to pyruvate ratio is disrupted and somehow leads to growth inhibition. This is supported by the observation that the addition of pyruvate to
αMG-stressed sgrS mutants actually caused lysis, as opposed to just growth inhibition, and that increasing conversion of pyruvate to PEP by ectopically expressing ppsA in an sgrS mutant prevented this lysis phenotype [151]. Depletion of PEP may also affect metabolism more broadly as PEP levels may be too low to regulate upstream glycolytic enzymes [130].
If sugar phosphate accumulation per se is not toxic, why does efflux contribute to stress relief? Kadner et al. report that ectopic expression of the uhpT transporter responsible for importing G6P and F6P also inhibited growth, which they attributed to accumulation of the toxic metabolite methylglyoxal or depletion of inorganic phosphate pools as a result of the sugar-phosphate/Pi antiporter activity [83]. Perhaps sugar phosphate toxicity only occurs when G6P is excess, but under depletion conditions such as glucose-phosphate stress it is beneficial to a point, after which efflux would prevent unnecessary accumulation of excess sugar phosphates. Furthermore, it is possible that once sugars are dephosphorylated by YigL they could be re-phosphorylated by glucokinase and further deplete energy within the cell [105]; efflux would prevent this from occurring.
Here, we have shown evidence that the multidrug efflux pump TolC may be the efflux pump responsible for ushering αMG out of cells during glucose-phosphate stress.
72 tolC mutants exacerbate αMG-induced growth inhibition in sgrS mutants (Figs. 4.3 and
4.4) and experience higher induction of the glucose-phosphate stress response (Fig. 4.2).
Most compelling is the preliminary finding that tolC mutants retain high levels of αMG, particularly when combined with a mutation in the yigL phosphatase (Fig. 4.5). More work must be done to explore the role of TolC under stress. First and foremost, repeating our αMG efflux assay would further solidify our finding that tolC mutants retain excess
αMG. To further test whether sugars are TolC substrates, particularly in sugar phosphate accumulating conditions, we would expect to see exacerbated growth inhibition when uhpC is ectopically expressed in cells growing on G6P. Additionally, we may observe a tolC mutant phenotype in growth media that worsens glucose-phosphate stress such as minimal glycerol with αMG; it is in these conditions that we observe a yigL growth defect [134].
TolC relies on nine associated inner membrane adaptors, most notably AcrAB, to pump substrates across the periplasm, however a strain lacking all nine adaptors had no phenotype on αMG with or without sgrS. Perhaps sugars use another means to access
TolC or perhaps other pumps are responsible for their efflux. We did test another multidrug efflux pump known to export sugars, MdfA [92], however, an mdfA mutant did not further exacerbate an sgrS growth defect in αMG (data not shown). Perhaps a more exhaustive examination of putative efflux pumps is necessary to exclude other possibilities.
73 4.4 Figures
Figure 4.1 Effects of the glycolytic intermediate glucose-6-phosphate on the uptake of [14C]αMG. (A) Wild-type (DJ480; squares) or (B) sgrS (CS123; circles) strains were 14 grown in liquid LB medium to an OD600 of 0.1, at which point [ C]αMG (10.0 μM; 3 μCi per sample) was added in either the absence (closed symbols, solid lines) or presence (open symbols, dotted lines) of G6P (1.38 μM). Cellular uptake of the radioactive [14C]αMG was measured at the indicated times. One representative example is shown (n = 3).
74
Figure 4.2 Effects of tolC mutants on the induction of PsgrS-lacZ expression during growth on αMG. WT (BAH100), sgrS (CL122), tolC (CL118), yigL (CL119), sgrS tolC (CL120), sgrS yigL (CL121), and sgrS tolC yigL (CL142) strains were grown overnight in TB, then subcultured 1:200 and grown to an OD600 of 0.1. Then cultures were split, with half receiving 0.5% αMG and the other half receiving an equivalent volume of ddH2O. Samples were taken after 120 minutes and β-galactosidase activity measured.
75
.
Figure 4.3 tolC mutants exacerbate growth defects on αMG in an sgrS background. WT (DJ480), sgrS (CS104), tolC (CL114), yigL (CL115), sgrS tolC (CL116), or sgrS yigL (CL117) cells were either grown on LB or on LB supplemented with 0.5% αMG overnight at 37°C.
76
Figure 4.4 tolC mutants exacerbate growth defects on αMG in an sgrS yigL background. WT (BAH100), sgrS (CL122), tolC (CL118), yigL (CL119), sgrS tolC (CL120), sgrS yigL (CL121), and sgrS tolC yigL (CL142) cells were grown on LB with 0.5% αMG overnight at 37°C.
77
Figure 4.5 tolC mutants retain radiolabled αMG. WT (BAH100), sgrS (CL122), tolC (CL118), yigL (CL119), sgrS tolC (CL120), sgrS yigL (CL121), and sgrS tolC yigL (CL142) cells were grown overnight in M63 glycerol (0.4%) with antibiotics at 37°C then subcultured (1:100) in 5 mL M63 glycerol to an OD600 of ~0.1 after which 1ml was harvested and given 1 μCi [14C]-αMG. Cells were incubated for 20 minutes at room temperature and efflux stimulated. Samples were vacuum filtered at 0, 20, 40, and 60 minutes post-efflux and [14C]-αMG retention measured by scintillation.
78 Chapter 5: Posttranscriptional regulation of the multidrug efflux pump MdfA by DicF contributes to growth inhibition and filamentation in E. coli
5.1 Introduction
The small RNA (sRNA) DicF is 53 nucleotides in length and encoded within the cryptic prophage Qin alongside a small protein, DicB. While one of the first sRNAs discovered in E. coli, its physiological role remains elusive [19]. Cryptic prophages have been shown to confer benefits to their hosts in various conditions; Qin has been shown to help cells resist the effects of the antibiotics azlocillin and nalidixic acid, specifically through DicB [179]. Whether DicF confers a benefit to cells is still unclear.
Ectopic expression of DicF inhibits growth and causes cell filamentation and bloating in rich LB media. Several mRNA targets of DicF have been characterized including ftsZ, xylR, pykA, and manX – yet no single target is solely responsible for growth inhibition [4, 10]. Posttranscriptional inhibition of ftsZ translation is responsible for filamentation since formation of the contractile Z-ring during cell division is halted.
However, cells expressing a DicF allele that regulates ftsZ (but not xylR or pykA) still filament, but are no longer growth inhibited; these data suggest that other targets contribute to growth inhibition irrespective of filamentation. DicF also negatively regulates xylR translation and ectopic expression of DicF inhibited growth on xylose as a sole carbon source. However, a DicF allele that differentially regulates xylR, but not ftsZ or pykA lost the filamentation and growth inhibition phenotypes in LB, further suggesting there are other targets that contribute to DicF-mediated growth inhibition [10].
This study used a combination of the latest computational and biochemical techniques to identify the new DicF target ahpC and discovered via old-fashioned
79 suppressor analysis that the multi-drug efflux pump MdfA partially contributes to DicF- mediated growth inhibition and filamentation.
5.2 Results
5.2.1 Prediction and validation of novel DicF targets using combined approaches
Previous efforts to identify new DicF targets included a combination of computational prediction and RNA-seq; these methods led to the discovery of pykA, xylR, and manX [10]. Trans-acting sRNAs like DicF use imperfect complementarity to regulate multiple targets, however this feature also makes accurate computational target prediction difficult. Furthermore, while RNA-seq alone provides a wealth of information about transcriptional changes during ectopic sRNA expression, meaningful physiological interactions can be difficult to parse out, particularly when the natural sRNA-expressing conditions are unknown. New approaches aimed at elucidating direct sRNA-mRNA interactions have been developed including MS2-affinity purification coupled with RNA sequencing (MAPS) [100] and RNA interaction by ligation and sequencing (RIL-seq)
[117]. MAPS utilizes an MS2 aptamer to tag the 5’ end of an sRNA for affinity purification; mRNA targets that co-purify with the tagged sRNA are identified with
RNA-seq. RIL-seq differs from MAPS in that it seeks to identify sRNA-mRNA pairs that are bound to the RNA chaperone Hfq – which is required by many sRNA-mRNA interactions. RIL-seq begins with in vivo crosslinking of RNAs bound to FLAG-tagged
Hfq. Cells are then lysed and Hfq is immunoprecipitated with an anti-FLAG antibody.
Lysates undergo a series of treatments to enrich for RNA pairs bound to Hfq; the RNA is then sequenced and analyzed through a computational pipeline [117].
80 We first collected RNA-seq data from a MAPS experiment conducted by David
Lalaouna and Eric Massé using MS2-tagged DicF (unpublished). These sequence read counts were normalized by coverage as indicated by the RPKM ratio and enrichment was plotted as a ratio of MS2-tagged DicF over untagged DicF versus that of MS2 tag and empty vector (Fig. 5.1 grey boxes). We defined targets of interest as those that were significantly enriched at a ratio of either >25 MS2-DicF/<5X MS2 (cyan triangles) or
>50 MS2-DicF/<5X MS2 (red triangles). The greater the enrichment of targets bound to
MS2-DicF relative to untagged DicF, the greater the likelihood the interaction was meaningful. For reference, all previously characterized targets are plotted as well, although none of the known targets met our cutoff standard for enrichment. We compiled a list of targets from our most stringent cutoff (>50 MS2-DicF/<5X MS2) and looked to see whether they were differentially regulated in previously performed DicF
RNA-seq experiments [10] (Table 5.2 A). Table 5.2A shows all of the targets that came from the most stringent cutoff (red triangles in figure 5.1) compared with their RNA-seq fold change and q-value. While these were the most highly enriched targets in the MAPS experiment, none of the targets met our typical cutoff for significance – a 3-fold change in either upregulation or downregulation and a q value of <0.05. Because we suspected that DicF may be targeting genes involved in cell division apart from ftsZ and because amiC was highly enriched and 2-fold upregulted in RNA-seq (with a q value of 0.001), we tested a amiC’-‘lacZ fusion for DicF regulation, but saw no difference (Fig. 5.5). We also selectively tested targets that showed >25 MS2-DicF/<5X MS2 enrichment in
MAPS that were also implicated in cell division such as bolA, but this target was not regulated either (Fig. 5.5).
81 Many of the predicted targets most stringently enriched in MAPS were internally transcribed tRNA spacers (ITS) from the metZ_metW or metW_metV tRNAs, which were not significantly regulated in our RNA-seq experiment. However, work by Lalaouna and
Massé showed these ITS elements can act as “sponges” that titrate sRNA regulators away from their mRNA targets once stress conditions that necessitate the sRNAs have passed
[100]. To test whether these ITS sponges act upon DicF, we ectopically produced wild type and mutant ITS sponges in combination with DicF from plasmids harboring inducible promoters; these were expressed in a strain containing a chromosomally
encoded ftsZ’-‘lacZ fusion under the control of a PBAD promoter as a readout of DicF regulation. Because DicF represses ftsZ, if the ITS sponges titrate DicF away from its target we would expect to see an increase in fusion activity, however, we saw no effect from ITS sponge expression on DicF repression (Fig. 5.4 stripes). We performed this titration assay on another target, xylR, but also saw no effect (data not shown). We also tested if ITS sponge expression rescued cells from DicF-mediated growth inhibition and saw no effect (data not shown).
We next turned to RIL-seq for identifying potential DicF targets since Melamed et al. included DicF in their experiments [117]. Unfortunately, the RIL-seq predictions did not include any previously verified DicF targets and although targets were predicted under various growth conditions, none of them had exceptionally high normalized odds ratios. In RIL-seq, the normalized odds ratio corresponds to sRNA-mRNA pairs that are statistically overrepresented as well as how enriched the pairs were on Hfq – the higher this ratio, the more likely the interaction is significant. For reference, the normalized odds ratio for the well characterized SgrS and ptsG 5’UTR interaction was 249.4 and the
82 highest ratio for any DicF target was 11.3. Nevertheless, we compared the list of targets identified by RIL-seq and included fold change values from our group’s DicF RNA-seq data [10]. This list included many ribosome-associated proteins and RNAs (Table 5.2 B).
To test whether DicF had a global effect on translation, a pulse-chase experiment was performed to measure differences in [35S] L-methionine incorporation in cells ectopically expressing DicF versus vector control. DB176 (ΔdicF) cells were grown in minimal glucose medium, then washed, and DicF (or vector control) was induced either 20 minutes before the pulse or during the pulse (Fig. 5.3). To initiate the pulse, [35S] L- methionine was added to cells and chased with 1 mM cold L-methionine plus TCA and
DTT to precipitate the protein in samples taken at ten minute increments for 50 minutes.
Samples were filtered and washed, then incorporation of radiolabeled methionine was measured via scintillation. We observed no difference between zero and 50 minutes (Fig.
5.3).
We decided to select targets for verification that were both predicted by RIL-seq and at least >25X MS2-DicF enriched in the MAPS analysis. Additionally, since we suspect DicF may be regulating division-involved genes other than ftsZ we included putative targets that were greater than 50X enriched in MAPS or computationally predicted and that had functions in cell division (Table 5.2 C). To test posttranscriptional regulation chromosomal translational lacZ fusions were constructed for each candidate target comprised of its 5’ UTR plus 30 amino acids from the coding region under the
control of an inducible PBAD promoter [115] (Fig. 5.5). Of all targets tested DicF significantly affected only ahpC and rpoS. A long fusion including the RIL-seq- predicted rpoS and DicF base pairing region (Fig. 5.5B) was tested and rpoS’-‘lacZ
83 activity decreased upon ectopic DicF expression. However, a short fusion eliminating this predicted base pairing region appeared to lose regulation (Fig. 5.5 A rpoS long versus short). This is contrary to what we observe in our RNA-seq experiment; here rpoS is upregulated (Fig. 5.2 C). In fact, the three known sRNAs shown to directly regulate rpoS are all positive regulators (their base pairing region are depicted in Fig. 5.5B). These results merit further investigation using more well-characterized rpoS’-‘lacZ fusions.
5.2.2 DicF posttranscriptionally represses ahpC
ahpC was identified both in RIL-seq and MAPS analysis and was the only such target to show significant regulation in our RNA-seq analysis (Figure 5.2 C) and in our reporter fusion (Fig. 5.5). While other targets were also predicted by both MAPS and
RIL-seq (rpoS, rplU, and rplN), these genes did not exhibit significant fold changes in our RNA-seq experiement (Fig. 5.2 C). To ensure the DicF effect on ahpC is direct, we used base pairing predictions from RIL-seq (courtesy of Dr. Hanna Margalit) [117] and from IntaRNA [23, 116] to select a mutant DicF allele that should interrupt pairing and lose regulation (Fig. 5.6 A). The interaction predicted by RIL-seq should be disrupted by the mutation in DicF3, while the IntaRNA predicted interaction might be disrupted by the mutation in DicF21 - both of these DicF mutants have been previously characterized
[10](Fig. 5.6 A). We tested these predictions using an ahpC’-‘lacZ translational fusion and found that both the wild type DicF and the DicF3 allele inhibited fusion activity ~4- fold relative to vector, while DicF21 is unable to repress the fusion (Fig. 5.6 B). This suggests that DicF directly represses ahpC and that IntaRNA most accurately predicted their interaction, which occurs near the ahpC RBS and suggests a canonical mechanism of regulation, although it is unclear why DicF21 was unable to repress this fusion as only
84 a single base pair in the predicted seed region was disrupted. Compensatory mutations are necessary to verify these results.
5.2.3 mdfA mutants partially suppress DicF-mediated growth inhibition and filamentation
While we identified a new DicF target, ahpC, we initially intended to identify targets involved in growth inhibition. To find such targets we turned to suppressor mutants. Because DicF is ectopically expressed from a plasmid we wanted to decrease the chance that suppressor mutants arose from the plasmid itself by producing DicF from two independent plasmids; we also included a chromosomal ftsZ’-‘lacZ translational fusion in our parent strain to test that at least one copy of plasmid-borne DicF remained functional. Parental (CL190) strains were grown on LB with antibiotic then independent colonies from different plates were re-streaked onto LB plates containing IPTG and aTc to induce DicF expression from each plasmid. Suppressors able to grow with ectopic production of DicF were isolated and their ftsZ’-‘lacZ fusions tested for maintained repression (Fig. 5.6 B). Suppressors that maintained functional DicF (numbered DSup1-
10, 13, 14) were monitored for growth in liquid culture alongside the parental strain (Fig.
5.6 A). These suppressors grew comparably well to their parental vector counterpart both on solid and in liquid media. In addition to growth, suppressors were submitted along side their parent strain for whole genome sequencing. Mutations were then mapped using
Breseq [33]. The only mutation found in all suppressors but absent in the parent strain was an IS1 insertion 75 nucleotides into the coding region of the mdfA gene. This suggested that disruption of mdfA could promote growth in the presence of ectopic production of DicF. To test this hypothesis, we made an mdfA mutation by P1 transduction of an mdfA::kan allele into the parent background. This mutation partially
85 suppressed DicF-mediated growth inhibition (Fig. 5.8 blue triangles versus red squares).
This mutation was not because of a polar effect since deleting the downstream gene ybjH had no suppressive effect (data not shown). To attempt to complement the mdfA mutation in the Dsup1 suppressor strain; the ybjH mutation linked to wild type mdfA was transduced back into Dsup1, however this did not fully restore sensitivity of the suppressor strain to DicF (Fig. 5.8 black circles). Together these data suggest that mdfA contributes to DicF-mediated growth inhibition, but that there are other contributing factors as well.
In addition to partially suppressing DicF-dependent growth inhibition, mdfA mutants also partially suppress filamentation (Fig. 5.9). While mdfA mutants still filament, their filaments appear shorter than in wild type cells. Interestingly, none of the ten DicF suppressors form filaments, however when mdfA was transduced back into
Dsup1, cells appeared slightly elongated (Fig. 5.9). These data further suggest that mdfA contributes to filamentation, but other genes contribute as well.
5.2.4 DicF posttranscriptionally upregulates mdfA mRNA
Because MdfA appears to play a role in DicF-mediated growth inhibition, we wanted to test if mdfA is target of DicF regulation. RNA-seq analysis revealed that mdfA is upregulated 1.64 fold (with a qValue of 1.59-13) when DicF is ectopically produced
[10]. We first predicted a base pairing interaction using IntaRNA [23] and found two predictions with the strongest being well within the coding region of mdfA 382 nucleotides from the +1 transcriptional start site (Fig. 5.10A). To test for posttranscriptional regulation we constructed a translational mdfA’-‘lacZ reporter fusion and ectopically expressed DicF or vector control, monitoring β-galactosidase activity as a
86 function of mdfA translation. Upon DicF expression, mdfA translation was enhanced
~1.75 fold compared to vector control (Fig. 5.10 B (black bars)). When the predicted base pairing region was excluded from the fusion, no increase in activity was observed
(Fig. 5.10 B (grey bars)). Our base pairing prediction suggested that our mutant DicF3 allele should lose the ability to regulate mdfA and when this allele was ectopically expressed no regulation was observed (Fig. 5.10 B). These data suggest DicF positively regulates mdfA. Additionally, we located mdfA in our MAPS analysis (Figure 5.1 purple circle).
5.2.5 mdfA mutants ectopically expressing DicF exhibit a growth advantage at alkaline pH
MdfA is an inner membrane antiporter that moves protons into the cytosol and sodium/potassium ions out of the cell. MdfA’s antiporter function has been shown to help cells adapt to alkaline conditions [108]. To this end, we wanted to test if DicF upregulation of mdfA may confer alkali tolerance. We tested mdfA mutant and wild type cell growth on a range of pHs from 7.0-9.0. Consistent with previous observations [108], mdfA cells harboring a vector control were more growth inhibited than wild type at pH
9.0 compared to 7.0 (Fig. 5.11). We also observed growth inhibition when ectopically expressing DicF in wild type cells at each pH (Fig. 5.11). Because MdfA has been shown to be important for cell growth at pH 9.0 and DicF upregulates mdfA we wanted to test conditions in which mdfA regulation might affect cell growth. Interestingly, we found that DicF promoted growth in the mdfA mutant at pH 9.0 relative to wild type cells.
Furthermore, as the pH increased from 8.0 up to 9.0 mdfA mutants expressing DicF experienced improved growth whereas wild type cells expressing DicF were consistently inhibited. While these data are consistent with our observation that an mdfA mutation
87 suppresses DicF growth inhibition, these data suggest that DicF is perhaps regulating another target that compensates for the loss of mdfA. To further investigate this, we tested a number of DicF mutant alleles for altered growth in an mdfA mutant background
(Fig. 5.12). At pH 7.0, DicF is severely inhibitory in both wild type and mdfA strains, however the DicF (DSup1) suppressor strain grew as well as vector controls.
Interestingly, the three DicF mutants: DicF3, DicF9, and DicF21 exhibited different growth patterns in an mdfA background. While wild type DicF was inhibitory in the mdfA background at pH 7.0, it was outgrown by DicF3, DicF9, and DicF21 with the latter two alleles growing the best. However, at pH 9.0 wild type DicF, DicF3, and DicF21 grew equally well with DicF9 outgrowing these alleles and all mdfA mutants harboring
DicF outgrowing vector control. While it is unclear what uncharacterized targets these
DicF mutants may no longer regulate that contribute to their differing abilities to grow at pH 7 and 9, we can conclude that DicF somehow confers a benefit to mdfA mutants at high pH that allows cells to outgrow wild type (Fig. 5.12).
5.3 Discussion
While sRNA regulators in bacteria are critical for fine-tuning the physiology of cells under various stress conditions, DicF causes deleterious growth inhibition and filamentation. Elucidating the DicF interactome will not only shed light on how cell physiology is altered by this sRNA, but if there are conditions in which it provides benefits to the cell. However, as this study shows, while there are many new tools aimed at identifying direct sRNA interacting partners, these methods are still imperfect as their best predictions resulted in many false positives (Figures 5.1-5.5) and only led to the validation of one novel negatively regulated target ahpC, which encodes alkyl
88 hydroperoxide reductase and is a member of the oxidative stress response (Figure 5.6).
However, this target was uninvolved in growth inhibition. By conducting suppressor mutant analysis, this study identified a gene that does contribute to growth - the positively regulated target mdfA, which encodes a multidrug efflux pump and proton sodium/potassium antiporter. When mutated, mdfA partially suppresses DicF-mediated growth inhibition and filamentation (Figures 5.8 and 5.9). Additionally we found that
DicF expression helps mdfA mutants grow at alkaline pH (Figures 5.11, 5.12). How regulation of these targets benefits the cell is still unclear partly because we still lack an understanding of when DicF is naturally expressed.
Multidrug efflux pumps have been shown to affect growth and cell division.
Overexpression of setB, a putative proton/sugar antiporter causes cell filamentation and deletion caused a delay in chromosome segregation [44]. Deletion of the acrEF, which encodes the inner membrane channels associated with the AcrEF-TolC efflux pump complex results in filamentation under conditions in which the similar AcrA protein is overproduced and that AcrEF also somehow play a role in chromosome segregation
[101]. MdfA has also been implicated in cell division as overexpression of mdfA at pH 6 is able to restore cell division and filamentation defects caused by a yqjA yghB double mutant, again by an unknown mechanism [159]; however these observations are contrary to ours.
How an mdfA mutation partially suppresses DicF-mediated growth inhibition, or rather, how DicF compensates for loss of mdfA in alkaline conditions is unclear. It is also unclear when DicF upregulation of mdfA is relevant if it is not sufficient to counteract the negative effects of DicF on growth in wild type cells under alkaline conditions. We
89 observed robust growth in the DicF suppressor mutant (Figure 5.12, DSup1) at both a neutral and alkaline pH suggesting there are other unidentified targets contributing to growth inhibition that are independent of pH. MdfA overexpression has shown to confer resistance to a number of antibiotics such as chloramphenicol, erythromycin, daunomycin, puromycin, benzalkonium, rifampin [38] while also conferring sensitivity to streptomycin [17]. Filamentation itself has also been shown to provide antibiotic resistance [18], which is certainly beneficial to cells. Additionally, filamentation helps uropathogenic E. coli (UPEC) resist host defenses during infection [81, 82], a strain that harbors the dicBF operon [10].
More work must be done to explore the interplay between DicF and MdfA as well as to identify other targets of DicF regulation. Because allowing cells to generate suppressor mutations on their own can result in multiple mutations that are difficult to parse out, we are currently using transposon mutagenesis to screen for DicF suppressors that may result in less complicated analysis. We are also exploring more ways to generate accurate sRNA target predictions using a combination of computational and experimental data. Our group is also attempting to identify regulators of the dicBF operon and conditions in which those regulators act. Perhaps this information will clarify the relevance of these new DicF targets and the potential benefits of DicF expression.
90 5.4 Figures
Figure 5.1 DicF MAPS analysis. MS2-affinity purification and sequencing (MAPS) was conducted with MS2-tagged DicF. mRNAs associated with DicF were sequenced and single-end reads were normalized to RPKM and plotted for enrichment versus controls. All targets are plotted in grey with the more highly enriched targets labeled in cyan triangles (>25X MS2-DicF and <5X MS2) and the most highly enriched targets labeled in red triangles (>50X MS2-DicF, <5X MS2). Previously confirmed DicF targets xylR, ftsZ, pykA, and manX are noted with circular dots. New targets ahpC and mdfA are also marked as cyan and purple circles, respectively.
91
Figure 5.2 DicF predicted targets from various methods. (A) DicF MAPS. Most highly enriched predicted targets from MAPS compared to our RNA-seq fold change and q value analysis. (B) DicF RIL-seq. RIL-seq predicted targets compared to our RNA-seq fold change and q value data. (C) Targets selected for verification of DicF posttranscriptional regulation using reporter gene translational fusions. The method(s) used to predict them are indicated as well as the fold change and q value data from our RNA-seq data.
92
Figure 5.3 Effect of ectopic DicF expression on protein synthesis. To test whether DicF expression affects global protein synthesis a pulse chase experiment was conducted.
Cells (DB176) were grown in minimal M63 glucose medium and washed then Plac-DicF expression was induced with 1 mM IPTG either prior to the pulse for 20 minutes (open symbols) or during the pulse (closed symbols). The pulse was initiated with the addition of [35S] L-methionine and the chase began by the addition of 1 mM cold L-methionine with 25% TCA and 1 mM DTT. Samples were taken immediately after the pulse at 0 minutes, then at 10 minute increments for 50 minutes. Samples were filtered and washed on a fiberglass disk with a vacuum manifold and incorporated radiolabeled methionine measured via liquid scintillation.
93
Figure 5.4 ITS sponge titration of DicF. To test whether ITS sponges could affect DicF target regulation, cells (CL190) with a chromosomally encoded arabinose-inducible ftsZ’-’lacZ fusion harbored various combinations of plasmids: an arabinose-inducible vector pNM12 or ITS derivatives combined with a tetracycline-inducible vector (pZA31 - solid) or DicF (stripes). Cells were grown in TB with antibiotics overnight, then subcultured 1:200 in TB with or without 0.1% L-arabinose and grown for 2 hours at 37 degrees C. DicF expression was then induced with 50 ng/ml aTc and beta-galactosidase activity was measured after 20 minutes and normalized to vector controls.
94
Figure 5.5 Validation of predicted DicF targets. (A) Chromosomally-encoded translational fusions were constructed from selected target candidates. Each candidate was fused to lacZ under the control of an arabinose-inducible promoter (PBAD) followed by the 5’ UTR and first 30 codons of the target gene. Β-galactosidase activity was assayed upon DicF expression from a plasmid. Specific activities were quantified in Miller units and normalized to vector controls to generate percent relative activity. (B) Schematic depicting predicted base pairing of DicF with rpoS compared to known sRNA regulators. rpoS’-’lacZ long fusion is indicated by the blue line and the short fusion indicated by the orange line.
95
Figure 5.6 Posttranscriptional regulation of ahpC by DicF alleles. (A) Base pairing predictions between DicF and ahpC mRNA by RIL-seq and Inta-RNA including locations of DicF3 and DicF21 alleles (B) β-galactosidase activity of an ahpC’-’lacZ fusion was assayed upon ectopic expression of wt DicF, DicF3, and DicF21 alleles. Specific activities were quantified in Miller units and normalized to vector controls to generate percent relative activity.
96
Figure 5.7 Growth of DicF suppressor strains. (A) Strains ectopically expressing DicF from two plasmids (Plac-dicF and Ptet-dicF) were grown in LB with antibiotic overnight, then subcultured 1:200 in LB and grown for one hour. Subsequently, DicF was induced with 50 ng aTc and 1 mM IPTG for 45 minutes, then aliquots of cells were transferred to a 48 well plate and grown in a plate reader. Growth curve is representative of 4 trials. Suppressors ectopically expressing DicF grew similarly well to wt vector control except for Dsup8, which consistently lagged. (B) Suppressors were checked for functional DicF by monitoring the inhibition of a chromosomal ftsZ’-‘lacZ fusion. β-galactosidase activity was measured upon dicF induction and percent activity was quantified relative to vector control.
97
Figure 5.8 mdfA partially suppresses DicF growth inhibition. (A) To test whether mdfA is responsible for suppressor (DSup1) DicF resistance, we transduced a wt copy of mdfA was transduced back into a suppressor (Dsup1 mdfA+ - closed circles). This made cells slightly more sensitive to Dic relative to the Dsup1 suppressor (diamonds). (B) An mdfA mutant was made in the suppressor parent strain and tested for DicF resistance versus wild type vector control (open circles). mdfA mutants in the parent had no effect on growth in vector controls (squares), but made cells more resistant to DicF (triangles) than the parent (open squares). Growth is plotted on a linear scale to highlight the differences between strains in stationary phase since their growth rates were equal.
98
Figure 5.9 mdfA mutants experience less DicF-mediated filamentation To test whether mdfA contributes to filamentation, an mdfA mutant was made in the suppressor parent strain (wt) and observed under a 40X EVOS XL microscope after 120 minutes of DicF or vector induction. Deletion of mdfA had no effect on morphology in vector control cells, but did appear to decrease the length of filamented cells upon DicF expression. Conversely, wt mdfA was replaced in suppressors with chromosomal mdfA mutations; Dsup1 mdfA+ cells were more elongated than Dsup1 cells. These data are consistent with the growth phenotypes and suggest MdfA somehow contributes to filamentation.
99
Figure 5.10 DicF posttranscriptionally upregulates mdfA. (A) Base pairing prediction between DicF and mdfA mRNA including location of DicF3 mutation. (B) β- galactosidase activity of an mdfA’-’lacZ fusion was assayed upon ectopic expression of wt DicF, and DicF3 alleles. Fusion activity was also assayed when the predicted base pairing region was excluded from the fusion (short fusion - grey bars). Specific activities were quantified in Miller units and normalized to vector controls to generate percent relative activity.
100
Figure 5.11 mdfA mutant sensitivity to DicF decreases in alkaline pH. mdfA and wild type strains ectopically expressing DicF or vector control from IPTG-inducible promoters were spotted at various dilutions on BTP-buffered LB at pH 7.0, 7.5, 8.0, 8.5, and 9.0. While mdfA mutants were as sensitive to DicF as wt cells at pH 7.0, at pH 9.0, DicF was beneficial to mdfA mutants allowing them to grow comparably well to wt cells harboring a control vector.
101
Figure 5.12 Effects of DicF alleles on mdfA growth at alkaline pH. (A) Schematic depicting wt DicF targets and locations and targets of DicF3, DicF9 and DicF21 alleles (B) mdfA and wild type strains ectopically expressing DicF or vector control from IPTG- inducible promoters were spotted at various dilutions on BTP-buffered LB at pH 7.0 and 9.0. While mdfA mutants outgrew wt cells expressing DicF at pH 9.0, mdfA cells expressing the DicF9 allele grew the strongest. mdfA DicF9 growth was comparable to mdfA cells complemented with mdfA overexpressed from a plasmid.
102 Chapter 6: Conclusions and future directions
Small RNAs perform diverse regulatory functions in E. coli physiology. Trans- encoded sRNAs are especially versatile; their short, imperfect base pairing regions allow them to posttranscriptionally regulate multiple mRNA targets positively or negatively and with varying degrees of intensity under a single stress condition. This can have far- reaching effects on physiology, which permits rapid adaptation to environmental changes.
Characterizing these targets and effects provides fundamental insight into bacterial physiology. Dual-function sRNA molecules exhibit even more versatility because they also encode proteins which can have either independent or redundant functions to the cognate sRNA [172]. In this dissertation, we explore the targets and effects of two small
RNA regulators, DicF and the dual-function sRNA SgrS, in an effort to further our understanding of E. coli physiology.
SgrS is a dual-function sRNA that acts during glucose-phosphate stress in which non-metabolizable sugars like αMG are transported into the cell and primed for glycolysis, but cannot proceed, resulting in growth inhibition. While the precise nature of this stress still remains unclear, the work described herein helped to determine it is not the accumulation of sugar phosphates per se that causes glucose-phosphate stress, but is more likely due to the depletion of glycolytic intermediates. Glucose-phosphate stress can be ameliorated with the addition of sugar phosphates downstream of the metabolic blockage and in Chapter 4 we showed that these sugar phosphates do not prevent further influx of αMG. This suggests phosphorylated sugars are not inherently toxic since rescue can occur even under accumulating conditions. While we lack an understanding of how this stress condition is detected by the stress response, the targets and mechanisms of
103 SgrS regulation are becoming well characterized. The base pairing or riboregulatory function of SgrS rescues cells from glucose-phosphate mediated growth inhibition by posttranscriptionally regulating a number of targets; this includes translational repression of the ptsG and manXYZ transporter mRNAs, which prevents synthesis of new transporters and further influx of non-metabolizable αMG. SgrS also enhances translation of the yigL mRNA that encodes a phosphatase necessary for the dephosphorylation of accumulated αMG-6-phosphate - which is required for efflux [16].
The efflux pump through which dephosphorylated αMG is flushed out of the cell has not been identified, but this study suggests the multidrug efflux pump TolC may be responsible. In Chapter 4, tolC mutants were characterized and found to exacerbate the
growth inhibition suffered by sgrS mutants. PsgrS-lacZ fusions also showed these mutants experience higher induction of the glucose-phosphate stress response. Additionally, efflux assays using radiolabled αMG show these mutants retain more αMG than an sgrS mutant. More work must be done to confirm that αMG is a TolC substrate and to test whether the glucose analog 2DG also accumulates in these mutants, since we suspect
αMG and 2DG cause growth inhibition by different mechanisms.
In addition to serving as an sRNA, SgrS also encodes the small protein SgrT, which can rescue cells from glucose-phosphate stress independently of SgrS base pairing
[175]. While we now have a clear understanding of how SgrT translation from the sgrS mRNA impacts SgrS riboregulation [11] and hypothesized that SgrT may affect the transport activity of the PtsG glucose permease [175], we did not know which transporter
(or transporters) SgrT targeted or how it rescued growth. In Chapter 3, we found that unlike SgrS, SgrT specifically targets the PtsG transporter and not the ManXYZ
104 transporter by directly and strongly inhibiting its transport activity. We also found SgrT localization to the membrane is dependent on PtsG. Furthermore, SgrT acts on highly stable, preexisting PtsG proteins that are unaffected by SgrS riboregualtion.
Interestingly, we observed transiently weak inhibition of the NagE N-Acetylglucosamine transporter, which is highly similar to PtsG. We used the fact that SgrT strongly and preferentially regulates PtsG over NagE to determine that the membrane domain of PtsG, and residues at the N terminus are required for SgrT sensitivity. Lastly, we found that
SgrT–mediated inhibition of PtsG transport activity overrides inducer exclusion, which is a mechanism the PTS protein EIIAGlc uses to prioritize glucose as a carbon source. We found that by preventing inducer exclusion under glucose-phosphate stress cells can utilize otherwise unfavorable sugars such as lactose to replenish glycolytic intermediates that were depleted during αMG transport and accumulation. While this work elucidated the role of SgrT during glucose-phosphate stress, there is still more to learn about this small protein. Studying the interaction between SgrT and PtsG is critical to understanding the mechanism of SgrT action, however, PtsG is a challenging membrane protein to work with and as a result there is very little structural information about it.
SgrT is also a challenging protein; because of its small size epitope tags often affect its activity. While we do utilize a functional 3X-FLAG tagged allele, this renders SgrT artificially stable relative to the untagged version (data not shown). In addition to structure-function studies, we lack an understanding of how SgrT is regulated. We have observed through Western blots using native α-SgrT antibodies that SgrT stability depends on PtsG. However, using a 3X-FLAG tagged SgrT, we find SgrT remains
105 functional, but is rendered artificially stable suggesting SgrT may be degraded by proteases.
Small proteins are not only remarkable because of their large effects on bacterial physiology, but because they possess such extraordinary target specificity given they are so limited in their primary sequence, and therefore their capability to interact with other proteins. We observed SgrT transiently regulated NagE, the GlcNAc transporter, that shares sequence similarity with PtsG. We have also previously observed that E. coli K12
SgrT orthologs are not highly conserved, with identities ranging from 84% (E. coli
CFT073) to 19% (Aeromonas hydrophila) [71]. What dictates target specificity remains an important question and whether any of these orthologs regulate NagE more or less transiently than our standard E. coli K12 SgrT. Can they regulate other sugar transporters or even multiple transporters and an SgrT be engineered to be a stronger regulator?
These are questions that will not only help us better understand small proteins, but may lead to practical applications of this understanding.
Compared to our understanding to SgrS, the small RNA DicF is relatively mysterious despite being one of the first sRNAs discovered. DicF is a non-coding sRNA, but is encoded in an operon with a small protein, DicB, located within a cryptic prophage.
Though we know DicF expression is deleterious in laboratory conditions, we have yet to discover conditions in which it is naturally expressed – and because it has been evolutionarily maintained in the chromosome, we suspect it must serve some benefit to the host. In elucidating the targets of DicF, we hope to understand how it functions and why; does it provide any benefit to the cell? While this study uncovered two new DicF targets, ahpC and mdfA, we still lack an understanding of how regulation of these and the
106 other known targets benefits E. coli physiology – since DicF expression inhibits cell growth and division. As described in chapter 5, we found that mutating the proton/sodium antiporter mdfA can partially suppress DicF-mediated growth defects and even provides a growth advantage compared to wild type cells when DicF is expressed in alkaline conditions. Because directed-mdfA-mutant suppression is partial compared to the suppressor mutants we isolated, we know other targets involved in growth have yet to be identified.
One key takeaway from this study is that despite advances in sRNA targetome- discovery methods, targets are still difficult to accurately predict and laborious to verify.
Additionally, it is often difficult to understand the physiological relevance of targets once they have been discovered. To this end we turned to classic genetic approaches to discover new targets. Because suppressor mutants can often be complicated, we are currently using transposon mutagenesis to find genes that may be involved in DicF- mediated growth inhibition. Our group is also developing a new tool to incorporate existing computational prediction programs with experimental data, such as RNA-seq, to more accurately predict targets; this will be utilized for DicF.
While there is still much to learn, this work contributed to our understanding of E. coli physiology and the finely tuned regulation that sRNAs and small proteins provide to quickly adapt to stress and environmental changes.
107 A protein called SgrT
Whose length was just 43
Plugged up a transporter in very short order
And its name was PtsG
DicF was a small RNA
That caused E. coli growth to decay
I was quite impressed
When DicF was suppressed
By mutations in mdfA
CRL
108
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