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bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Vitamin and auxotrophy in anaerobic consortia operating under methanogenic

condition

Valerie Hubalek*1, Moritz Buck*1,2, BoonFei Tan3,4, Julia Foght3, Annelie Wendeberg5, David

5 Berry6, Stefan Bertilsson1, Alexander Eiler*#1,7

1 Department of Ecology and , Limnology and Science for Life Laboratory, Uppsala

University, Sweden

2 NBIS, National Bioinformatics Infrastructure Sweden, Uppsala, Sweden

10 3 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada

4 Center for Environmental Sensing and Modeling, Singapore-MIT Alliance for Research and

Technology

5 Centre for Environmental Research, Environmental , Leipzig, Germany

6 Department of Microbiology and Ecosystem Science, Division of , University

15 of Vienna, Vienna, Austria

7 eDNA solutions AB, Mölndal, Sweden

* contributed equally

20 # Corresponding author: Correspondence and requests for materials should be addressed to

Alexander Eiler [email protected]

1 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Abstract

Syntrophy among and facilitates the anaerobic degradation of organic

25 compounds to CH4 and CO2. Particularly during aliphatic and aromatic

mineralization, as in crude oil reservoirs and -contaminated sediments, metabolic

interactions between obligate mutualistic microbial partners are of central importance1.

Using micro-manipulation combined with shotgun metagenomic approaches, we

disentangled the genomes of complex consortia inside a short chain -degrading

30 cultures operating under methanogenic conditions. Metabolic reconstruction revealed that

only a small fraction of genes in the metagenome-assembled genomes of this study, encode

the capacity for of facilitated by energy conservation linked to H2

. Instead, inferred lifestyles based on scavenging anabolic products and

intermediate fermentation products derived from detrital biomass was a common feature in

35 the consortia. Additionally, inferred auxotrophy for and amino acids suggests that

the hydrocarbon-degrading microbial assemblages are structured and maintained by

multiple interactions beyond the canonical H2-producing and syntrophic alkane degrader–

partnership2. Our study uncovers the complexity of ‘interactomes’ within

microbial consortia mediating hydrocarbon transformation under anaerobic conditions.

40

Microbial consortia that degrade under anaerobic conditions hold the potential to

influence hydrocarbon profiles with either adverse or beneficial effects on the recovery and

refining of oil3–5. In environmental restoration, microbial degradation is seen as an effective and

environmental-friendly treatment of oil-contaminated sites. Still, in anaerobic systems,

45 efforts are challenged by low efficiency and poor success. Additionally there is a

severe problem with unwanted contamination of adjacent systems with pollutants such as toxic

2 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

metals, naphthenic acids and polycyclic aromatic compounds6–8 as well as accelerated release of

the potent greenhouse gas from the biodegradation process9.

Analyses of chemical profiles and metagenomic data from hydrocarbon-degrading consortia

50 maintained in laboratory-scale cultures10–15 have identified some of the organisms and the

metabolic pathways involved in the anaerobic degradation of various hydrocarbons, such as

alkanes, benzenes and naphthalenes14,19-21,16,17. The anaerobic degradation of hydrocarbons is

usually a two- to three-step process involving fermentation either to simple substrates for

(, formate, , CO2) or to other metabolites (e.g. lactate, ,

55 propionate, butyrate, fatty acids) that can undergo secondary fermentation yielding

aforementioned simple methanogenic substrates18–20.

Still, we are far from having a detailed understanding of the molecular mechanisms that

establish and maintain such syntrophic methanogenic consortia where deplete the

partial pressure of hydrogen facilitating the fermentation process by making it thermodynamically

60 favourable. Additional members of the consortium that scavenge metabolic byproducts and

thereby participate in the biodegradation process as secondary consumers, have thus far been

overlooked21 and their additional functions in the consortia remain hidden. One possible role of

such scavengers could be as providers of essential to salvage other consortia members

from auxotrophies while they also alter the thermodynamic equilibrium. It previously has been

65 suggested that inability of individual community members to synthesize the full range of organic

nutrients required for growth may be a favourable trait for communities and consortia operating

under energy-limited conditions1. Reconstructing metabolic pathways and assigning functions

among community members using genomics is a first step towards a more holistic understanding

of microbial consortia mediating anaerobic degradation of hydrocarbons2.

70 For this study, we extracted high-quality genomes of syntrophic bacteria from public

databases. To identify taxa that have the potential to grow syntrophically, we used gene

annotations predicting enzymes involved in reverse and direct electron transfer. Many syntrophic

3 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

bacteria are known to rely on the capacity to perform reverse electron transport-driven energy-

conserving H2 production through electron-confurcating hydrogenase (H2ase) in combination with

75 reduced ferredoxin21. Our analysis confirmed a wide distribution of membrane-bound, ion-

translocating ferredoxin:NAD+ oxidoreductase and confurcating hydrogenase that could directly

couple the oxidation of NADH and reduced ferredoxin to produce hydrogen (Suppl. Tab. 1).

Additionally, most of the putatively syntrophic bacterial isolates lacked important genes involved

in biosynthesis of one or more amino acids and vitamins, indicating that they rely on precursors

80 (or the co-factors) provided by other bacteria to produce fully functional enzymes with required

cofactors and prosthetic groups (Suppl. Fig. 1).

Next, we attempted to resolve these interactions beyond the available genomes in public

databases by isolating natural methanogenic consortia. Short-chain alkane degrading enrichment

cultures (SCADCs) from mature fine tailings of the Mildred Lake Settling Basin13 were used to

85 obtain 13 shotgun metagenomes from various subcultures of the original enrichment culture (for

details on the metagenomes see suppl. Tab. 2). The cultures have previously been described in

several metagenomic studies inferring the broader metabolic roles and identity of the community

members at the phylum level13 (for taxonomic composition see Suppl. Fig. 2). These included

eight samples where each individual sample contained approximately ten individually picked

90 filaments, pooled based on the presence or absence of visible epibionts. The physical manipulation

for sequencing was an attempt to isolate members of the consortia that exchange co-factors or

their precursors in close physical contact such as syntrophs, versus free-living community

members with peripheral roles in alkane degradation.

From the pool of ~80 selected filaments, we obtained a metagenome co-assembly of

95 805606 scaffolds totaling ~1 Gbp with an N50-length of 4902 bp using MEGAHIT. Downstream

coverage and nucleotide composition-based binning of the 150698 scaffolds of at least 1000 bp

length, resulted in 307 bins with 45 matching our criteria for being defined as high-quality

metagenome assembled genomes (MAGs). As indicated by detailed annotations of these MAGs

4 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

using the ‘MicroScope’ pipeline22, the most likely hydrocarbon degraders in the culture are

100 putative syntrophic bacteria related to Syntrophus, Pelotomaculum, Desulfobacterium and

Clostridium, all having the potential for n-alkane activation, betaoxidation and fumarate

regeneration. The genes indicative for these pathways were alkylsuccinate synthase and

benzylsuccinate synthase (C-H activation), methylmalonyl CoA mutase (carbon skeleton

rearrangement) and methylmalonyl-CoA decarboxylase (decarboxylation) for n-alkane activation;

105 enoyl-CoA hydratase, β-hydroxyacyl-CoA dehydrogenase and acyl-CoA acetyl-transferase for

beta-oxidation; propionyl-CoA carboxylase, methylmalonyl-CoA mutase, succinyl-CoA

synthetase and succinate dehydrogenase for fumarate regeneration14. Most genomes encoded

enzymes associated with fermentation and coupled pathways for acetogenesis (i.e. reductive

acetyl-CoA or Wood-Ljungdahl pathway), a process by which acetate is produced from CO2 and

110 an electron donor (Figure 1). The five methanogen genomes reconstructed from the contig bins

belonged to the genera Methanoculleus and Methanosaeta in the class Methanomicrobia and to

the class Thermoplasmata As previously described, Methanosaeta represent the acetoclastic

methanogens while Methanoculleus represent hydrogenotrophic methanogens, and

Thermoplasmata represent methylotrophic methanogens23. Besides these differences in substrates

115 used for methane production, they all encode complete sets of nitrogen fixation genes. For detailed

exploration of the genomes we direct the reader to the online sources of the ‘MicroScope’

pipeline22 where each genome’s individual KEGG and biocyc maps can be inspected.

In addition to classical syntrophic interactions described in hydrocarbon-degrading

communities, i.e. where one partner produces metabolites such as H2, acetate, ethanol and/or small

120 organic intermediates, which are then used by methanogens and secondary degraders, our genomic

reconstructions point to additional metabolic dependencies. Firstly, the scavenging of metabolic

products derived from detrital biomass is indicated by the presence of genes encoding transporters

for a wide diversity of and fatty acids, as well as genes involved in the degradation of

intermediate fermentation products (i.e. C1 compounds and alcohols) (Figure 2). Genomes of

5 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

125 these secondary degraders belonged to the deltaproteobacterial genera Desulfovibrio,

Desulfomicrobium and Desulfobulbus previously reported to use H2, organic acids, formate, or

short-chain alcohols as electron donors for sulfate reduction24–26. In addition to their potential to

grow by using anaerobic respiration, these genera possessed genes associated with fermentation of

a wide range of alcohols and organic acids such as lactate, amino and carboxylic acids.

130 Like many of their cultivated and genome sequenced relatives, the MAGs from the putative

sulfate reducers in these consortia revealed auxotrophies for vitamins and amino acids (Figure 3).

Even though the absence of pathways, defined by less than half of the genes present in the

respective pathways, need to be assessed with caution because of the partial nature of the

individual MAGs, analogous auxotrophies in closely related MAGs and closed genomes from

135 public databases provide strong support for widespread auxotrophy. Examples of essential

metabolite pathways whose biosynthetic gene distribution is patchy in the SCADC MAGs are

those for biosynthesis of vitamins B6 (pyridoxal), B12 (adenosylcobalamin), and H (biotin).

Earlier large-scale genome sequence analyses have previously suggested that corrinoids, essential

cofactors for vitamins27, are widely shared by over 70% of the sequenced bacterial , while

140 less than 25% of species synthesize corrinoids de novo28,29. The existence of over a dozen

structurally distinct corrinoids produced and used by various Bacteria and Archaea30 can thus hold

a central role in dictating microbial community assembly and functioning, as it is clear that the

structure of the precursor, which can be a benzimidazole, purine or a phenolic compound30,

influences the degree to which a particular corrinoid can be used by a given organism31,32.

145 Likewise, the absence of genes underlying biosynthesis of essential amino acids is apparent

in particular taxonomic groups (Figure 3B). The loss of essential biosynthesis function in various

taxonomic groups has previously been associated with energy- and -limitation selecting for

small cells with reduced genomes such as found in the open ocean and deep biosphere33,34.

Particularly costly functions are absent in most members of the SCADC community, resulting in a

150 community critically depending on essential metabolite providers. Biosynthesis of certain vitamins

6 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

such as adenosylcobalamin and specific amino acids such as phenylalanine, tyrosine and

tryptophan, is energetically costly and require a large set of genes. This loss of function and

subsequent adaptations to a cooperative lifestyle under nutrient- and energy-limitation forms the

foundation for the Black Queen hypothesis35.

155 In the context of the SCADC, the Black Queen hypothesis implies that, in addition to

fermentation products disposal by methanogens, other types of “public goods” can be exchanged.

Such "public goods" are provided by a few taxa hosting the enzymes to perform this energetically

costly biosynthesis while benefitting the other organisms in their vicinity. This enhanced cross

feeding is logical if one considers the need for metabolic processes to be optimized for reduced

160 metabolic burden at the level of an individual cell living at the thermodynamic limit.

To conclude, we show that the interactome of syntrophic alkane degrader–methanogen

partnerships surpass the standard electron- and simple carbon compound-transfer. Biosynthesis of

vitamins and other energy-expensive metabolites seem to be unequally distributed among

community members and we propose that this facilitate energy conservation at the thermodynamic

165 limit. It can be further speculated that and amino acid augmentations could possibly

enhance petroleum bioaugmentation processes in remediation of hydrocarbon-contaminated sites.

Methods

Culturing. An enriched short-chain alkane-degrading culture (SCADC) was enriched from mature

170 fine tailings of the Mildred Lake Settlings Basin as detailed by Tan et al.13. In short, the primary

enrichment cultures were established in multiple replicates by adding 25 ml oil sand tailings to 50

36 ml of mineral methanogenic medium , under a headspace of O2-free 30% CO2–N2 balance gas.

After an initial 1-year incubation in the dark at room temperature, the primary cultures were

pooled and used to inoculate multiple replicates of first transfer cultures into fresh methanogenic

175 medium. After a second 6-month incubation, these cultures were pooled as an inoculum for the

experimental SCADC enrichment cultures, where 0.1% (v/v) of an alkane mixture comprising

equal volumes of C6-C9 compounds was added to the community and incubated at least 4 months

7 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

at 28 °C in the dark, prior to further subculturing13. The samples analyzed in the present study

were from several transfers of the parent SCADC culture. Three bottles containing 75-ml cultures

180 were each sampled three times using micromanipulation, originally to capture filamentous bacteria

seen to carry attached smaller cocci (Fig. 1). Fluorescence in situ hybridization (FISH) using

probes MX825b and MX825c37 revealed that most filaments represent Methanosaeta with

associated bacterial cells.

185 Filament sampling. Micromanipulation was performed using an Eppendorf TransferMan® NK 2

at the Department of Microbial Ecology, University of Vienna. Each slide used for

micromanipulation was prepared by cleaning with “DNA AWAY” surface decontaminant

(ThermoFisher Scientific) and rinsed in sterile phosphate-buffered saline. Filaments were picked

from a 12 µl culture subsample by using microscopy (Axio Observer.D1, Zeiss) at 32x

190 magnification, captured in a 4 µm diameter capillary (TransferTip®, Eppendorf) and subsequently

transferred into a sterile tube. Approximately 10 filaments were collected from each of eight

cultures and pooled according to coherent morphology.

Samples with pooled filaments (n = 8) were then lysed by subjecting them to four freeze-

thaw cycles, freezing at -80°C followed by heat treatment at 70°C for 5 minutes. These samples

195 were subjected to whole genome amplification with multiple displacement amplification (MDA)

using the REPLI-g® Mini kit according to the manufacturer’s instructions (Qiagen).

Whole culture DNA isolation. From the SCADC culture, 100 ml were filtered through 0.2 µm

Supor® Membrane Disc Filters (Pall). Prior to bead beating, the above mentioned freeze-thaw cell

200 lysis was conducted, as preceding tests showed that the filaments needed a more vigorous

treatment. The DNA was then isolated from the filters by bead-beating using the PowerSoil®

DNA Isolation Kit (MoBio) according to the manufacturer’s instructions, and sequenced as

8 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

described below. No whole genome amplification with multiple displacement amplification

(MDA) was performed on these samples.

205

Library preparation and sequencing. The SciLifeLab SNP/SEQ sequencing facility at Uppsala

University performed the library preparation and the sequencing. First, 10 ng of genomic DNA

was sheared using a focused ultrasonicator (Covaris E220). The sequencing libraries were

prepared with the Thruplex FD Prep kit (Rubicon Genomics) according to manufacturer’s

210 protocols (R40048-08, QAM-094-002). Library size selection was made using AMPpure XP

beads (Beckman Coulter) in 1:1 ratio with the DNA sample volume. The prepared sample libraries

were quantified using KAPA Biosystems next-generation sequencing library qPCR kit and

analysing using a StepOnePlus (Life Technologies) real-time PCR instrument. The quantified

libraries were then prepared for sequencing on the Illumina HiSeq sequencing platform with a

215 TruSeq paired-end cluster kit, v3, and Illumina’s cBot instrument to generate a clustered flowcell

for sequencing. Sequencing of the flowcell contents was performed using an Illumina HiSeq2500

sequencer with Illumina TruSeq SBS sequencing kit v3, following a 2x100 indexed high-output

run recipe.

220 Assembly and binning of metagenome reads. Reads were filtered based on their quality scores

using Sickle (version 1.210)38. The read-set was digitally normalized using khmer

(arXiv:1203.4802) and subsequently assembled with MEGAHIT39. Contigs were scaffolded with

the BESST software40. Coverage was computed by mapping back the reads to the scaffolds using

bbmap (BBMap - Bushnell B. - sourceforge.net/projects/bbmap/) and for computing coverage,

225 bedtools (version 2.18.2)41 was used. Scaffolds were binned using MetaBAT

(doi:10.7717/peerj.1165) The criteria for high quality bins, so-called MAGs, are based on

CheckM(doi:10.1101/gr.186072.114) estimates of completeness (>70%) and contamination

(<5%).

9 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

230 Processing of mined data. In addition to data acquired from the newly sequenced samples, we also

accessed three datasets from the same original SCADC, downloaded from the NCBI Short Read

Archive (SRA): SRR636559 (a high depth HiSEQ dataset), and SRR634694 and SRR634695 (two

Roche 454 datasets). These archival sequences were treated bioinformatically in the same way as

the new sequences and co-assembled with them.

235

Annotation. Initial phylogenetic attribution of the MAGs was performed using PhyloPhlAn42 on

proteins predicted with Prokka (version 1.9)43, supplemented with a custom set of MAGs, single

amplified genomes (SAGs) and whole genome sequences accessed from JGI IMG/M. PFAM

annotations were performed using the Pfam database 27.044 and HMMER45 (version 3.1b1) with

240 default parameters. Detailed genome annotation analyses were performed using the ‘MicroScope’

pipeline22 with automatic annotations assisted by manual curation as described in the integrated

bioinformatics tools and the proposed annotation rules. Reconstructed MAGs are deposited on

MicroScope platform22 with identifier ‘scadc_MAG’.

245 Acknowledgements

We acknowledge the Uppsala Multidisciplinary Center for Advanced Computational Science

(UPPMAX) for access to data storage and computing resources under project b2013274. This

work was supported by the Swedish Research Council VR (Grant 2012-4592 to AE and 2012-

3892 to SB), the Swedish Foundation for Strategic Research (Grant ICA010-015 to AE), Swedish

250 Research Council Formas (project 2012-986 to SB) and the Helmholtz Initiative and Networking

Fund.

1 0 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

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Figure and Tables

Figure 1. A phylogenomic tree of recovered genomes as computed by PhyloPhlAn41. The

colorstrip delineates taxonomic affiliation. The symbols show the metabolic traits, based on

370 genome annotations. Traits with high support are indicated by closed symbols, while traits with

low support have open symbols, and categories with missing symbols indicate that no indications

of the trait were found. The two barcharts on the far right show the number of contigs assigned to

each bin and the assembly size (in Mbp) contained in the recovered genome bins.

375 Figure 2. Model of potential metabolic pathways and metabolic cross-feeding in the short-chain

alkane degrading culture (SCADC) representing (green) archaeal filaments, (blue) alkane

degraders, (red) intermediate metabolite scavengers and secondary degraders, (grey) acetogenic

bacteria. In addition, the figure shows the inferred syntrophic interactions from hydrogen (green),

carbon dioxide (dark blue) and acetate (green) to intermediate fermentation metabolites (IFMs;

380 violet) transfer as well as other forms of metabolic interdependencies such as cross-feeding of

costly metabolites such as vitamins (red) and amino acids (black).

Figure 3. Heat map of amino acid (A) and vitamin (B) biosynthetic capabilities of taxonomic bins

obtained from the short-chain alkane degrading culture (SCADC). Prototrophy predictions for

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385 each amino acid and vitamin are based on 'pathway completion' value i.e, the number of reactions

for pathway x in a given organism/total number of reactions in the same pathway x defined in the

MetaCyc or KEGG databases. Value of 1/0 indicates all/none of the key enzymes involved in the

biosynthesis. Dendograms represent clustering based on potential biosynthesis profiles. To verify

widespread auxotrophy for vitamins and amino acids in syntrophic prokaryotes, a similar analysis

390 was performed using genomes available from genera representing our taxonomic bins (for details

see Supplementary Figure 1). As a definition of absence we used a threshold of less than 0.5

pathway completeness.

Supplementary Material

395 Supplementary Figure 1. Heat map of amino acid (A) and vitamin (B) biosynthetic capabilities of

selected genomes obtained from MaGe. Prototrophy predictions for each amino acid and vitamin

are based on 'pathway completion' value i.e, the number of reactions for pathway x in a given

organism/total number of reactions in the same pathway x defined in the MetaCyc or KEGG

databases. Value of 1/0 indicates all/none of the key enzymes involved in the biosynthesis.

400 Dendograms represent clustering based on potential biosynthesis profiles. This resembles wide

spread auxotrophy for vitamins and amino acids as inferred for the short-chain alkene degrading

culture (SCADC).

Supplementary Figure 2. Taxonomic composition of the SCADC in the different samples used for

405 shotgun metagenomic sequencing. The 16S rRNA gene Data was produced following the

procedure as outlined in Sinclair et al. (2015).

Supplementary Table 1. Distribution of membrane-bound, ion-translocating ferredoxin:NAD+

oxidoreductase and confurcating hydrogenase that could directly couple the oxidation of NADH

410 and reduced ferredoxin to produce hydrogen.

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Supplementary Table 2. Source of metagenome and summary of sequencing data. “+Epibiont” indicates samples including filaments with epibioints whereas “-Epibioints” without epibionts.

1 7 bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/128660; this version posted April 19, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.