SEARCH · Search bioRxiv

Results for “Microbiology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources

bioRxiv2022

Rapid and accurate identification of Escherichia coli STEC O157:H7 by mass spectrometry, artificial intelligence and detection of specific biomarkers peaks.

The different pathotypes of Escherichia can produce a large number of human diseases. Surveillance becomes complex since their differentiation are not easy. Particularly, the detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157:H7 consists of stool culture of a diarrheal sample in enrichment and/or selective media, identification of presumptive colonies and confirmation by Multiplex PCR technique for the genotypic characterization of serogroup O157 and Shiga toxins (stx1 and stx2), in addition to the traditional biochemical identification. All of these procedures are laborious, require a certain level of training, are time consuming and expensive. Among the currently most widely used methodologies, MALDI-TOF MS mass spectrometry (matrix-assisted laser desorption/ionization with time-of-flight mass detection), allows a quick and easy way to obtain a protein spectrum of a microorganism, not only in order to identify the genus and species, but also the discovery of potential biomarker peaks of a certain characteristic. In the present work, the information obtained from 60 clinical isolates was used to detect peptide fingerprints of STEC O157:H7 and other diarrheagenic E. coli. The differences found in the protein profiles of the different pathotypes established the foundations for the development and evaluation of classification models through automated training. The application of the Biomarkers in combination with the predictive models on a new set of samples (n=142), achieved 99.3% of correct classifications, allowing the distinction between STEC O157:H7 isolates from the other diarrheal Escherichia coli. Therefore, given that STEC O157:H7 is the main causal agent of haemolytic uremic syndrome and based on the performance values obtained in the present work (Sensitivity=98.5% and Specificity=100%), this development could be a useful tool for diagnosis of the disease in clinical microbiology laboratories.

microbiology↗

bioRxiv2022

Ultra-high-throughput microbial single-cell whole genome sequencing for genome-resolved metagenomics

Microbes exist widely in nature. However, less than 1% of the species of microorganisms have been discovered so far, and more than 99% of microorganisms still remain unknown, which is called microbial dark matter. Unravelling microbial dark matter is not only helpful for exploring the unknown microbial world, but also of great significance for human health research. Ever since a long time ago, due to technical limitations, the microbiome, to a great extent, is still a black box. The traditional population-based metagenomic analysis tools are without single microbial resolution and they are stretched when studying rare and unknown microbial species. Here, we use high-throughput microdroplet technology to achieve the whole genome amplification of microbial single-cell genomes in pico-litter sized microdroplets, and develop subsequent library preparation steps such as indexing of the genome, to achieve the development of ultra-high-throughput microbial single-cell whole genome sequencing for genome-resolved metagenomics, aiming to provide a powerful new weapon for exploring microbial dark matter and other microbiological studies.

microbiology↗

bioRxiv2022

Advancing antimicrobial resistance monitoring in surface waters with metagenomic and quasimetagenomic methods

Surface waters present a unique challenge for the monitoring of critically important antimicrobial resistance. Metagenomic approaches provide unbiased descriptions of taxonomy and antimicrobial resistance genes in many environments, but for surface water, culture independent data is insufficient to describe critically important resistance. To address this challenge and expand resistome reporting capacity of antimicrobial resistance in surface waters, we apply metagenomic and quasimetagenomic (enriched microbiome) data to examine and contrast water from two sites, a creek near a hospital, and a reservoir used for recreation and municipal water. Approximately 30% of the National Antimicrobial Resistance Monitoring Systems critically important resistance gene targets were identified in enriched data contrasted to only 1% in culture independent data. Four different analytical approaches consistently reported substantially more antimicrobial resistance genes in quasimetagenomic data compared to culture independent data across most classes of antimicrobial resistance. Statistically significant differential fold changes (p<0.05) of resistance determinants were used to infer microbiological differences in the waters. Important pathogens associated with critical antimicrobial resistance were described for each water source. While the single time-point for only two sites represents a small pilot project, the successful reporting of critically important resistance determinants is proof of concept that the quasimetagenomic approach is robust and can be expanded to multiple sites and timepoints for national and global monitoring and surveillance of antimicrobial resistance in surface waters.

microbiology↗

bioRxiv2022

Microbial population dynamics decouple nutrient affinity from environmental concentration

How the growth rate of a microbial population responds to the environmental availability of chemical nutrients and other resources is a fundamental question in microbiology. Models of this response, such as the widely-used Monod model, are generally characterized by a maximum growth rate and a half-saturation concentration of the resource. What values should we expect for these half-saturation concentrations, and how should they depend on the environmental concentration of the resource? We survey growth response data across a wide range of organisms and resources. We find that the half-saturation concentrations vary across orders of magnitude, even for the same organism and resource. To explain this variation, we develop an evolutionary model to show that demographic fluctuations (genetic drift) can constrain the adaptation of half-saturation concentrations. We find that this effect fundamentally differs depending on the type of population dynamics: populations undergoing periodic bottlenecks of fixed size will adapt their half-saturation concentration in proportion to the environmental resource concentration, but populations undergoing periodic dilutions of fixed size will evolve half-saturation concentrations that are largely decoupled from the environmental concentration. Our model not only provides testable predictions for laboratory evolution experiments, but it also reveals how an evolved half-saturation concentration may not reflect the organisms environment. In particular, this explains how organisms in resource-rich environments can still evolve fast growth at low resource concentrations. Altogether our results demonstrate the critical role of population dynamics in shaping fundamental ecological traits.

microbiology↗

bioRxiv2022

A novel rRNA hybridization-based approach to rapid, accurate Candida identification directly from blood culture

Invasive fungal infections are increasingly common and carry high morbidity and mortality, yet fungal diagnostics lag behind bacterial diagnostics in rapidly identifying the causal pathogen. We previously devised a fluorescent hybridization-based assay to identify bacteria within hours directly from blood culture bottles without subculture, called phylogeny-informed rRNA-based strain identification (Phirst-ID). Here, we adapt this approach to unambiguously identify 11 common pathogenic Candida species, including C. auris, with 100% accuracy from laboratory culture (33 of 33 strains in a reference panel, plus 33 of 33 additional isolates tested in a validation panel). In a pilot study on 62 consecutive positive clinical blood cultures from two hospitals that showed yeast on Gram stain, Candida Phirst-ID matched the clinical laboratory result for 58 of 59 specimens represented in the 11-species reference panel, without misclassifying the 3 off-panel species. It also detected mixed Candida species in 2 of these 62 specimens, including the one discordant classification, that were not identified by standard clinical microbiology workflows; in each case the presence of both species was validated by both clinical and experimental data. Finally, in three specimens that grew both bacteria and yeast, we paired our prior bacterial probeset with this new Candida probeset to detect both pathogen types using Phirst-ID. This simple, robust assay can provide accurate Candida identification within hours directly from blood culture bottles, and the conceptual approach holds promise for pan-microbial identification in a single workflow.

microbiology↗

bioRxiv2022

Competition-cooperation in the chemoautotrophic ecosystem of Movile Cave - first metagenomic approach on sediments

BackgroundMovile Cave (Dobrogea, SE Romania) hosts a subterranean chemoautotrophically-based ecosystem supported by a sulfidic thermal aquifer analogous to the deep-sea hydrothermal ecosystems. Our current understanding of Movile Cave microbiology has been confined to the thermal water proximity (no more than 2 m distant), with most studies focusing on the water-floating mat, which likely acts as the primary production powerhouse in this sulfidic ecosystem. To gain more insightful information on the functioning of the sulfidic Movile Cave ecosystem, we employed a metagenomics-resolved approach to reveal the microbiome diversity, metabolic potential, and interactions and infer its roles within the food webs in the sediments beyond the sulfidic thermal waters. ResultsA customized bioinformatics pipeline led to the recovery of 106 high-quality metagenome-assembled genomes from 7 cave sediment metagenomes. Assemblies taxonomy spanned 19 bacterial and three archaeal phyla with Acidobacteriota, Chloroflexota, Proteobacteria, Planctomycetota, Ca. Patescibacteria, Thermoproteota, Methylomirabilota, and Ca. Zixibacteria as prevalent phyla. Functional gene analyses allowed prediction of CO2 fixation, methanotrophy, sulfur and ammonia oxidation as possibly occurring in the explored sediments. Species Metabolic Coupling Analysis of metagenome-scale metabolic models revealed the highest competition-cooperation interactions in the sediments collected at the farthest distance from the sulfidic water. As a result of simulated metabolic interactions, autotrophs and methanotrophs were hypothesized as major donors of exchanged metabolites in the sediment communities. Cross-feeding dependencies were assumed only towards currency molecules and inorganic compounds (O2, PO43-, H+, Fe2+, Cu2+) in the sediment nearby sulfidic water, whereas hydrogen sulfide and methanol are predictably traded exclusively among communities dwelling in the distant gallery. ConclusionsThese findings suggest that the primary production potential of the Movile Cave expands way beyond its hydrothermal waters, enhancing our understanding of ecological interactions inside chemolithoautotrophically based subterranean ecosystems and their functioning.

microbiology↗

bioRxiv2022

Ecological Dynamics Imposes Fundamental Challenges in Microbial Source Tracking

Quantifying the contributions of possible environmental sources ("sources") to a specific microbial community ("sink") is a classical problem in microbiology known as microbial source tracking (MST). Solving the MST problem will not only help us understand how microbial communities were formed, but also have far-reaching applications in pollution control, public health, and forensics. Numerous computational methods, referred to as MST solvers hereafter, have been developed in the past and applied to various real datasets to demonstrate their utility across different contexts. Yet, those MST solvers do not consider microbial interactions and priority effects in microbial communities. Here, we revisit the performance of several representative MST solvers. We show compelling evidence that solving the MST problem using existing MST solvers is impractical when ecological dynamics plays a role in community assembly. In particular, we clearly demonstrate that the presence of either microbial interactions or priority effects will render the MST problem mathematically unsolvable for any MST solver. We further analyze data from fecal microbiota transplantation studies, finding that the state-of-the-art MST solvers fail to identify donors for most of the recipients. Finally, we perform community coalescence experiments to demonstrate that the state-of-the-art MST solvers fail to identify the sources for most of the sinks. Our findings suggest that ecological dynamics imposes fundamental challenges in solving the MST problem using computational approaches.

microbiology↗

bioRxiv2022

Molecular epidemiology of carbapenemase-producing Acinetobacter spp. from Israel, 2001-2006: earliest report of blaNDM predating the oldest known blaNDM-positive strains

BackgroundCarbapenem-resistant Acinetobacter baumannii (CRAb) is a WHO priority 1 critical pathogen. Despite early emergence of elevated CRAb rates in Israel, limited molecular data from this location are available. We searched for carbapenemases among 198 clinical Acinetobacter spp. from Israel between 2001 and 2006. MethodsStrains from 3 archives underwent whole-genome sequencing (Illumina NovaSeq on all, MinION on a subset) and computational analyses: assembly (Unicycler), annotation (prokka), identification (Kraken, rpoB similarity), search for carbapenemases (ResFinder, BLDB curation). FindingsA. baumannii (Ab) represented 179 (90{middle dot}4%) Acinetobacter spp. Eighty-four Ab (46{middle dot}9%) carried a carbapenemase: 38 (45{middle dot}2%) blaOXA-72 (blaOXA-24-like); 28 (33{middle dot}3%) blaOXA-23-like (20 blaOXA-23 and 8 blaOXA-225); 18 (21{middle dot}5%) blaOXA-58 (16 from 2001-2). Carbapenemase rates increased yearly from 2002 (32%) to 2006 (67%). Eight species of non-baumannii Acinetobacter (NbA) accounted for 19 isolates (9{middle dot}6%). Two of three A. junii contained blaOXA-58, one of which, Ajun-H1-3, isolated in January 2004, also possessed blaNDM-1. The pNDM-Ajun-H1-3 plasmid matched numerous NDM-positive plasmids reported from 2005 onwards in Acinetobacter spp. as well as Enterobacterales. InterpretationWe assessed carbapenemase diversity among Acinetobacter spp. in Israel from 2001-2006. Findings in Ab predate observations elsewhere: rapidly rising carbapenemase rates, driven by blaOXA-23-like and blaOXA-24-like genes replacing blaOXA-58. Among NbA, an A. junii isolated in 2004 carried blaNDM-1, making it the earliest NDM-positive isolate reported to date, preceding those from 2005 in India. Further research into blaNDMs emergence is warranted, in order to shed light on the evolution and spread of this and other antibiotic-resistance genes. FundingCentre de recherche Charles-Le Moyne; Department of Microbiology and Infectious Diseases, Faculty of Medicine and Health Sciences, Universite de Sherbrooke; Fonds de recherche du Quebec - Sante; New Frontiers in Research Fund Grant NFRFE-2019-00444; CIFAR-Azrieli Global Scholars Program.

microbiology↗

bioRxiv2022

Enhancement of the Activity of the Antimicrobial Peptides HNP1 and LL-37 by Bovine Pancreatic Ribonuclease A

BackgroundHNP1, LL-37, and HBD1 are antimicrobial against Escherichia coli ATCC 25922 at the standard inoculum but less active at higher inocula. MethodsThe virtual colony count (VCC) microbiological assay was adapted for high inocula and the addition of yeast tRNA and bovine pancreatic ribonuclease A (RNase). 96-well plates were read for 12 hours in a Tecan Infinite M1000 plate reader and photographed under 10x magnification. ResultsAdding tRNA 1:1 to HNP1 at the standard inoculum almost completely abrogated activity. Adding RNase 1:1 to HNP1 at the standard inoculum of 5x105 CFU/mL did not enhance activity. Increasing the inoculum to 6.25x107 CFU/mL almost abrogated HNP1 activity. However, adding RNase 25:1 to HNP1 enhanced activity. Adding both tRNA and RNase resulted in enhanced activity, indicating that the enhancement effect of RNase overwhelms the inhibiting effect of tRNA when both are present. HBD1 activity at the standard inoculum was almost completely abrogated by the addition of tRNA, but LL-37 activity was only slightly inhibited by tRNA. At the high inoculum, LL-37 activity was enhanced by RNase. HBD1 activity was not enhanced by RNase. RNase was not antimicrobial in the absence of antimicrobial peptides. Cell clumps were observed at the high inoculum in the presence of all three antimicrobial peptides and at the standard inoculum in the presence of HNP1+tRNA. ConclusionsAntimicrobial peptide-ribonuclease combinations have the potential to be active against high cell concentrations and biofilms, conditions where the antimicrobial agent alone is relatively ineffective.

microbiology↗

bioRxiv2022

Differential metabolism between biofilm and suspended Pseudomonas aeruginosa cultures in bovine synovial fluid by 2D NMR-based metabolomics

Total joint arthroplasty is a common surgical procedure resulting in improved quality of life; however, a leading cause of surgery failure is periprosthetic joint infection. Periprosthetic infection often involves biofilms, making treatment challenging. Periprosthetic joint infections are difficult to diagnose by traditional culturing methods and there are no clinical biomarkers for the presence of biofilms. Further, the metabolic state of pathogens in the joint space is difficult to diagnose, the mechanism of their tolerance to antibiotics and host defenses is not well understood, and their culturing in the laboratory is challenging. Thus, there is a critical need for improved pathogen- and phenotype-specific diagnosis as well as improved treatment strategies toward better patient outcomes. Here, we present a quantitative, untargeted NMR-based metabolomics strategy for Pseudomonas aeruginosa suspended culture and biofilm phenotypes grown in bovine synovial fluid. We identified 21 unique metabolites as potential markers of P. aeruginosa and one unique marker of the biofilm phenotype in synovial fluid. Significant differences in metabolic pathways were found between the suspended culture and biofilm phenotypes including creatine, glutathione, alanine, and choline metabolism and the tricarboxylic acid cycle. These unique metabolite and pathway differences have the potential to serve as targets for P. aeruginosa and specifically biofilm diagnosis and biofilm control in synovial fluid. Author SummaryJoint replacement surgery is a common procedure frequently required in later stages of life due to damage in the joint. Over one million joint replacement surgeries are performed annually with rates increasing every year. A devastating complication associated with joint replacement is the development of infection around the implant device in the joint space, known as a periprosthetic joint infection. Bacteria in the joint space can form a biofilm, which is a gel-like matrix encasing the cells that increases resistance to treatment and exacerbates chronic infections. A particular challenge for the diagnosis of biofilm-mediated periprosthetic joint infections is the slowly growing nature of biofilm-mediated phenotypes, resulting in frequent failure to detect these bacteria by clinical microbiological culturing methods. Small molecule metabolites are uniquely produced by strains of bacteria in the biofilm versus planktonic or suspended culture phenotype. Identification of metabolites as specific markers of infection and biofilm could allow a new culture-free diagnostic approach to diagnose infection by biofilm. Furthermore, knowledge of metabolic pathway populations in biofilm in joint fluid could point to specific targets to prevent biofilm formation in the joint space.

microbiology↗

bioRxiv2022

A novel time-lapse imaging method for studying developing bacterial biofilms

In nature, bacteria prevailingly reside in the form of biofilms. These elaborately organized surface-bound assemblages of bacterial cells show numerous features of multicellular organization. We recently showed that biofilm growth is a true developmental process, which resembles developmental processes in multicellular eukaryotes. To study the biofilm growth, in a fashion of eukaryotic ontogeny, it is essential to define dynamics and critical transitional phases of this process. The first step in this endeavor is to record the gross morphological changes of biofilm ontogeny under standardized conditions. This visual information is instrumental in guiding the sampling strategy for the later omics analyses of biofilm ontogeny. However, none of the currently available visualizations methods is specifically tailored for recording gross morphology across the whole biofilm development. To address this void, here we present an affordable Arduino-based approach for time-lapse visualization of complete biofilm ontogeny. The major challenge in recording biofilm development on the air-solid interphase is water condensation, which compromises filming directly through the lid of a Petri dish. To overcome these trade-offs, we developed an Arduino microcontroller setup which synchronizes a robotic arm, responsible for opening and closing the Petri dish lid, with the activity of a stereomicroscope-mounted camera and lighting conditions. We placed this setup into microbiological incubator that maintains temperature and humidity during the biofilm growth. As a proof-of-principle, we recorded biofilm development of five Bacillus subtilis strains that show different morphological and developmental dynamics.

microbiology↗

bioRxiv2022

L-norepinephrine induces ROS formation but alters microbial community composition by altering cellular metabolism

Neuroendocrine compounds discharged into wastewater systems represent an emerging challenge at the intersection of human physiology and environmental microbiology. L-norepinephrine (L-NE) L-NE, which has been recognized to potentiate growth of human and animal bacterial pathogens, is discharged in sewage through urine and feces. While extensive pure culture studies have established L-NEs capacity to modulate bacterial virulence through iron acquisition and quorum sensing pathways, its impact on complex microbial communities, where intricate metabolic networks and interspecies interactions dominate, remains largely unexplored. This knowledge gap is particularly critical as urbanization drives increasing neuroendocrine compound loads in wastewater influents in metropolitan areas. Through parallel treatments of L-NE (1x10{square}{square} to 1x10{square}{square} M), dextrose, and H{square}O{square} in municipal and agricultural wastewater communities, we uncovered sophisticated metabolic and regulatory mechanisms that challenge the conventional understanding of microbial substrate utilization. Despite containing 10-fold less carbon, L-NE treatments achieved superior growth (10{square} CFU mL{square}{superscript 1}) while maintaining Pseudomonadaceae-dominated communities. Targeted metaproteomics revealed coordinated upregulation of oxidative stress genes (oxyR, soxRS) and antioxidant enzymes, while proteome-constrained metabolic modeling demonstrated distinct pathway modulation in central carbon and nitrogen metabolism. Notably, when compared to dextrose-supplemented controls representing typical carbon substrate utilization, L-NE treatments showed similar taxonomic profiles without preferential enrichment of known pathogenic families. However, L-NE significantly enhanced autoinducer gene (luxS, qseC) expression, suggesting increased virulence potential through community-level metabolic reprogramming. These findings reveal L-NE as a potent modulator of microbial community dynamics in engineered ecosystems, with important implications for treatment process stability and downstream environmental impacts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/482069v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1d80968org.highwire.dtl.DTLVardef@51cb63org.highwire.dtl.DTLVardef@b37org.highwire.dtl.DTLVardef@e07503_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOTOC FigureC_FLOATNO C_FIG

microbiology↗

bioRxiv2022

A case of mycobacteriosis associated with Mycobacterium pseudoshottsii in aquarium-reared fish in Japan

In 2019, several aquarium-reared fish died at a sea life park in Japan. Necropsy revealed micronodules on the spleen in the dotted gizzard shad (Konosirus punctatus). Seven of 16 fish exhibited microscopic multifocal granulomas associated with acid-fast bacilli in the spleen, kidney, liver, alimentary tract, mesentery, gills, and/or heart. Bacterial cultures yielded isolates from the dotted gizzard shad and a Japanese sardine (Sardinops melanostictus). Microbiological examination, multilocus sequence typing analysis, and variable number of tandem repeats analysis with a newly proposed 6-loci set revealed the isolates as Mycobacterium pseudoshottsii. To our knowledge, this is the first isolation of M. pseudoshottsii from aquarium-reared fish.

microbiology↗

bioRxiv2022

DNA methyltransferase enhanced Fusobacterium nucleatum genetics

Bacterial restriction-modification (R-M) systems are a first line immune defense against foreign DNA from viruses and other bacteria. While R-M systems are critical in maintaining genome integrity, R-M nucleases unfortunately present significant barriers to targeted genetic modification. Bacteria of the genus Fusobacterium are oral, Gram-negative, anaerobic, opportunistic pathogens that are implicated in the progression and severity of multiple cancers and tissue infections, yet our understanding of their direct roles in disease have been severely hindered by their genetic recalcitrance. Here, we demonstrate a path to overcome these barriers in Fusobacterium by using native DNA methylation as a host mimicry strategy to bypass R-M system cleavage of user introduced plasmid DNA. We report the identification, characterization, and successful use of Fusobacterium nucleatum (Fn) Type II and III DNA methyltransferase (DMTase) enzymes to produce a multi-fold increase in gene knockout efficiency in the strain Fusobacterium nucleatum subsp. nucleatum 23726 (Fnn 23726), as well as the first efficient gene knockouts and complementations in Fnn 25586. We show plasmid protection can be accomplished in vitro with purified enzymes, as well as in vivo in an E. coli host that constitutively expresses Fnn DMTase enzymes. By characterizing specific DMTases that are critical for bypassing R-M systems, we have enhanced our understanding of potential enzyme combinations, with the goal of expanding these studies to genetically modify clinical isolates of Fusobacterium that have thus far been inaccessible to molecular characterization. This proof-of-concept study provides a roadmap to guide molecular microbiology efforts of the scientific community to facilitate the discovery of new Fusobacterium virulence genes, thereby leading to a new era of characterizing how an oral opportunistic pathogen contributes to an array of human infections and diseases. IMPORTANCEFusobacterium nucleatum is an oral opportunistic pathogen associated with diseases including cancer and preterm birth. Our understanding of how this bacterium modulates human disease has been hindered by a lack of genetic systems. Here we show that F. nucleatum DNA methyltransferase modified plasmid DNA overcomes the transformation barrier and allows the development of genetic systems in previously inaccessible strains. We present a strategy that can be expanded to enable the genetic modification of clinical isolates, thereby fostering investigational studies to uncover novel host-pathogen interactions in Fusobacterium.

microbiology↗

bioRxiv2022

A ready-to-use logistic Verhulst model implemented in R shiny to estimate growth parameters of microorganisms

In microbiology, the estimation of the growth rate of microorganisms is a critical parameter to describe a new strain or characterize optimal growth conditions. Traditionally, this parameter is estimated by selecting subjectively the exponential phase of the growth, and then determining the slope of this curve section, by linear regression. However, for some experiments, the number of points to describe the growth can be very limited, and consequently such linear model will not fit, or the parameters estimation can much lower and strongly variable. In this paper, we propose a tools to estimate growth parameters using a logistic Verhulst model that take into account the entire growth curve for the estimation of the growth rate. The efficiency of such model is compared to the linear model. Finally, the novelty of our work is to propose a "Shiny-web application", online, without any programming or modelling skills, to allow estimating growth parameters including growth rate, maximum population, and beginning of the exponential phase, as well as an estimation of their variability. The final results can be displayed in the form of a scatter plot representing the model, its efficiency and the estimated parameters are downloadable.

microbiology↗

bioRxiv2022

Bacterial droplet-based single-cell RNA-seq reveals heterogeneity in bacterial populations and in response to antibiotic perturbation

We introduce BacDrop, a highly scalable technology for bacterial single-cell RNA sequencing that has overcome many challenges hindering the development of scRNA-seq in bacteria. BacDrop can be applied to thousands or millions of cells from both gram-negative and gram-positive species. It features universal ribosomal RNA depletion and combinatorial barcodes that enable multiplexing and massively parallel sequencing. We applied BacDrop to study Klebsiella pneumoniae clinical isolates and to elucidate their heterogeneous responses to antibiotic stress. In an unperturbed population presumed to be homogenous, we find within- population heterogeneity largely driven by the expression of mobile genetic elements that promote the evolution of antibiotic resistance. Under antibiotic perturbation, BacDrop revealed transcriptionally distinct subpopulations associated with different phenotypic outcomes including antibiotic persistence. BacDrop thus can capture cellular states that cannot be detected by bulk RNA-seq, which will unlock new microbiological insights into bacterial responses to perturbations and larger bacterial communities such as the microbiome.

microbiology↗

bioRxiv2022

Hydrogen and dark oxygen drive microbial productivity in diverse groundwater ecosystems

Groundwater ecosystems are globally wide-spread yet still poorly understood. We investigated the age, aqueous geochemistry, and microbiology of 138 groundwater samples from 87 monitoring wells (<250m depth) located in 14 aquifers in the Canadian Prairie. Geochemistry and microbial ecology were tightly linked revealing large-scale aerobic and anaerobic hydrogen, methane, nitrogen, and sulfur cycling carried out by diverse microbial communities. Older groundwaters contained on average more cells (up to 1.4x107/mL) than younger ground-waters. Organic carbon-rich strata featured some of the highest abundances, challenging current estimates of global groundwater population sizes. Substantial concentrations of dissolved oxygen (n=57; 0.52{+/-}0.12 mg/L [mean{+/-}SE]; 0.39 mg/L [median]) in older groundwaters could support aerobic lifestyles in subsurface ecosystems at an unprecedented scale. Metagenomics, oxygen isotope analyses and mixing models indicated that microbial "dark oxygen" contributed to the dissolved oxygen pool in subsurface ecosystems commonly assumed to be anoxic.

microbiology↗

bioRxiv2022

Termite diet rather than geographical origin determines the microbiome composition and functional genetic structure of nests from South American and African representatives, as revealed by a multiomics approach

Termites represent one of the most important insect groups worldwide due to their key role as plant decomposers and proxy of carbon recycling in the tropical rainforest ecosystems. Besides, high relevance in research has been given to these social insects due to a prominent role as urban pests. However, one of the most fascinating aspects of termites are their defence strategies that prevent the growth of detrimental microbiological strains on their nests. One success factor is the key role of the nest allied microbiome. Understanding how beneficial microbial strains aid termites in pathogen biocontrol strategies could provide us with an enhanced repertoire for fighting antimicrobial resistant strains or mine for genes for bioremediation purposes. We carried out a multiomics approach for dissecting the nest microbiome in a wide range of termite species, covering several feeding habits and three geographical locations at two tropical sides of the Atlantic Ocean, and an African savanna. Our experimental approach included untargeted volatile metabolomics, targeted evaluation of volatile naphthalene, taxonomical profile for bacteria and fungi through amplicon sequencing, and further dive into the genetic repertoire through a metagenomic sequencing approach. Volatile naphthalene was present in species belonging to the genera Nasutitermes and Cubitermes. We further assessed the apparent differences in terms of bacterial community structure, having found a stronger influence from feeding habits and genera, rather than the geographical location. Lastly, our metagenomic analysis revealed that the gene content provides both soil feeding genera with similar functional profiles, while the wood feeding genus shows a different one. These results seem to be independent of the geographical location, indicating that the nest functional profile is heavily influenced by the diet of the termite inhabiting, building, and maintaining the nest.

microbiology↗