Do Organic Substrates Drive Microbial Community Interactions in Arctic Snow? Benoît Bergk Pinto, Lorrie Maccario, Aurélien Dommergue, Timothy Vogel, Catherine Larose To cite this version: Benoît Bergk Pinto, Lorrie Maccario, Aurélien Dommergue, Timothy Vogel, Catherine Larose. Do Or- ganic Substrates Drive Microbial Community Interactions in Arctic Snow?. Frontiers in Microbiology, Frontiers Media, 2019, 10, 10.3389/fmicb.2019.02492. hal-02415106 HAL Id: hal-02415106 https://hal.archives-ouvertes.fr/hal-02415106 Submitted on 8 Jan 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. fmicb-10-02492 October 30, 2019 Time: 16:16 # 1 ORIGINAL RESEARCH published: 31 October 2019 doi: 10.3389/fmicb.2019.02492 Do Organic Substrates Drive Microbial Community Interactions in Arctic Snow? Benoît Bergk Pinto1*, Lorrie Maccario1†, Aurélien Dommergue2, Timothy M. Vogel1 and Catherine Larose1* 1 Environmental Microbial Genomics, Laboratoire Ampère, École Centrale de Lyon, UMR CNRS 5005, Université de Lyon, Lyon, France, 2 Univ Grenoble Alpes, CNRS, IRD, Grenoble INP, Institut des Géosciences de l’Environnement, Grenoble, France The effect of nutrients on microbial interactions, including competition and collaboration, has mainly been studied in laboratories, but their potential application to complex ecosystems is unknown. Here, we examined the effect of changes in organic acids among other parameters on snow microbial communities in situ over 2 months. We Edited by: compared snow bacterial communities from a low organic acid content period to that Brian D. Lanoil, University of Alberta, Canada from a higher organic acid period. We hypothesized that an increase in organic acids Reviewed by: would shift the dominant microbial interaction from collaboration to competition. To Jeremy Dodsworth, evaluate microbial interactions, we built taxonomic co-variance networks from OTUs California State University, San Bernardino, United States obtained from 16S rRNA gene sequencing. In addition, we tracked marker genes of Feng Ju, microbial cooperation (plasmid backbone genes) and competition (antibiotic resistance Westlake Institute for Advanced Study genes) across both sampling periods in metagenomes and metatranscriptomes. Our (WIAS), China results showed a decrease in the average connectivity of the network during late spring *Correspondence: Benoît Bergk Pinto compared to the early spring that we interpreted as a decrease of cooperation. This [email protected] observation was strengthened by the significantly more abundant plasmid backbone Catherine Larose [email protected] genes in the metagenomes from the early spring. The modularity of the network from †Present address: the late spring was also found to be higher than the one from the early spring, which is Lorrie Maccario, another possible indicator of increased competition. Antibiotic resistance genes were Microbiology Section, Department significantly more abundant in the late spring metagenomes. In addition, antibiotic of Biology, University of Copenhagen, Copenhagen, Denmark resistance genes were also positively correlated to the organic acid concentration of the snow across both seasons. Snow organic acid content might be responsible for this Specialty section: This article was submitted to change in bacterial interactions in the Arctic snow community. Extreme Microbiology, Keywords: competition, cooperation, networks, snow, organic acids a section of the journal Frontiers in Microbiology Received: 01 June 2019 INTRODUCTION Accepted: 16 October 2019 Published: 31 October 2019 Dynamic changes in nutrient concentrations have been shown to influence bacterial interactions Citation: with ramifications for microbial community structure and function (Friedman and Gore, Bergk Pinto B, Maccario L, 2017; Khan et al., 2018). In these pure culture studies, either cooperation or competition Dommergue A, Vogel TM and was the dominant interaction strategy depending on the nutrients considered and their Larose C (2019) Do Organic Substrates Drive Microbial concentrations (Brockhurst et al., 2008, 2010, Lambert et al., 2011, 2014; Ravindran, 2017). Community Interactions in Arctic Interference competition was hypothesized to be mediated by antibiotic release (Cornforth Snow? Front. Microbiol. 10:2492. and Foster, 2013; Oliveira et al., 2015; Ponce-Soto et al., 2015; Song et al., 2017) doi: 10.3389/fmicb.2019.02492 and was shown to be affected by the nutrient supply (Hol et al., 2014). For example, Frontiers in Microbiology| www.frontiersin.org 1 October 2019| Volume 10| Article 2492 fmicb-10-02492 October 30, 2019 Time: 16:16 # 2 Bergk Pinto et al. Organic Acids Drive Bacterial Interactions a sensitive Escherichia coli strain was observed to co-exist with explored by recent experiments that show a differential growth a colicin-secreting E. coli strain when co-cultivated on a poor rate of environmental bacterial strains when co-cultured with growth medium (sugars), but not on a rich medium (amino acids other specific strains (Pande et al., 2014; Ren et al., 2015; and peptides), where the colicin-secreting E. coli strain released Vartoukian et al., 2016). Bacterial interactions could provide antibiotics (Hol et al., 2014). Cooperation was also proposed to a selective advantage to bacterial species as a function of be mediated by either metabolic or genetic exchanges between nutrient concentrations and subsequently influence bacterial different collaborative strains (Nogueira et al., 2009; Mc Ginty community structure. et al., 2011; Dimitriu et al., 2014, 2015; Benomar et al., 2015; Tracking bacterial interactions in situ can be performed Wall, 2016; Tecon and Or, 2017) and has also been shown to through networks, such as co-variance networks based on be affected by nutrient supply (Benomar et al., 2015). Several taxonomic data (Faust and Raes, 2012). This approach has studies have examined the importance of horizontal gene transfer been used for microbial communities from oceans (Ruan, in maintaining cooperation in synthetic bacterial communities 2006; Lima-Mendez et al., 2015), soils (Barberán et al., 2012; (Czárán and Hoekstra, 2009; Nogueira et al., 2009; Dimitriu Ding et al., 2015), human microbiomes (Faust et al., 2012) et al., 2014, 2015; Wall, 2016). Therefore, cooperation might be and heavy-metal-polluted sediments (Yin et al., 2015). These promoted by increasing assortment among cooperative alleles networks often use co-variance to infer positive (cooperative) (Dimitriu et al., 2014) or by increasing kin selection (Nogueira and negative (competitive) bacterial interactions (e.g., Ruan, et al., 2009; Wall, 2016). In addition, most of the genes coding 2006), but co-variance might also indicate that the populations for public goods appeared to be preferentially localized on are responding to other stimuli, simultaneously. An approach mobile genetic elements (plasmids) and at hotspots of genome combining gene markers for bacterial interactions based on recombination (Nogueira et al., 2009). pure culture studies and taxonomy-based co-variance networks The majority of research concerning nutrient-related effects described above should strengthen the results obtained. Here, on bacterial interactions has been generated with culture-based we applied this combined approach using antibiotic resistance experiments (Mitri and Foster, 2013). While these studies as the surrogate for competition and plasmid structural genes have provided information on different nutrient effects on for collaboration, and taxonomy-based co-variance networks on bacterial interactions under controlled conditions, they might not microbial communities sampled from an Arctic snowpack over predict microbial interactions in the environment. Microcosm the spring season. Arctic snow microbial communities were or mesocosm approaches have been used more recently to study selected because arctic snow carbon content varies by several microbial communities and the results have varied (Ponce-Soto orders of magnitude during the spring season (Twickler et al., et al., 2015; Ali et al., 2016; Song et al., 2017). Although no 1986) and is generally considered a low carbon environment. studies concerning the effect of carbon content on microbial Recently, using COG functions characteristic of oligotrophy interactions have been published to date, one study measured an or copiotrophy as proposed by Lauro et al.(2009), Maccario increase in antibiotic resistance genes in strains of Enterococcus et al.(2019) showed that arctic snow bacterial communities faecalis cultivated in eutrophic sediment mesocosms amended were adapted to oligotrophic lifestyles. However, oligotrophic with nitrogen and phosphorus (Ali et al., 2016). Other studies the arctic snow environment is, carbon content increases over observed a decline of antibiotic resistance in cultivable bacterial the spring season (Hacking et al., 1983; Twickler et al., 1986; populations from an oligotrophic lake in mesocosms amended Haan et al., 2001; Grannas et al., 2007). In addition, Arctic snow with