Biology subjects

Knight, R.

Publications and source records attributed to Knight, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Fish microbiomes 101: disentangling the rules governing marine fish mucosal microbiomes across 101 species

Fish are the most diverse and widely distributed vertebrates, yet little is known about the microbial ecology of fishes nor the biological and environmental factors that influence the fish microbiome. The microbiota from 101 species of Southern California marine fishes, spanning 22 orders, 55 families, and 83 genera representing ~25% of local marine fish diversity, was analyzed to identify patterns that explain microbial diversity patterns in a geographical subset of marine fish biodiversity. We compared fish microbiomes (gill, skin, midgut, and hindgut) using alpha, beta, and gamma diversity along with establishing a novel method to estimate microbial biomass (Qiime2 plugin katharoseq). For oceanic fishes from the neritic zone, host size and distance from shore were negatively associated with microbial biomass densities and diversity in the gills. Body site was the strongest driver for beta diversity with strong evidence of phylosymbiosis observed across the gill, skin, and hindgut, but not midgut. The majority of microbes from all fish body sites were of unknown origin but overall sea water generally contributes more microbes to fish mucus compared to marine sediment. In a meta-analysis of vertebrate hindguts (569 species), mammals had the highest gamma diversity when controlling for host species number while fishes had the highest percent of unique microbial taxa (92%). In fishes, the midgut, gill, and skin contains the majority of microbial diversity which collectively can be 5.5 times higher than the hindgut. The composite dataset will be useful to vertebrate microbiome researchers and fish biologists interested in microbial ecology with applications in aquaculture and fisheries management.

ecology↗

bioRxiv2022

A comparison of six DNA extraction protocols for 16S, ITS, and shotgun metagenomic sequencing of microbial communities

Microbial communities contain a broad phylogenetic diversity of organisms, however the majority of methods center on describing bacteria and archaea. Fungi are important symbionts in many ecosystems, and are potentially important members of the human microbiome, beyond those that can cause disease. To expand our analysis of microbial communities to include fungal ITS data, we compared five candidate DNA extraction kits against our standardized protocol for describing bacteria and archaea using 16S rRNA gene amplicon- and shotgun metagenomics sequencing. We present results considering a diverse panel of host-associated and environmental sample types, and comparing the cost, processing time, well-to-well contamination, DNA yield, limit of detection, and microbial community composition among protocols. Across all criteria, we found the MagMAX Microbiome kit to perform best. The PowerSoil Pro kit performed comparably, but with increased cost per sample and overall processing time. The Zymo MagBead, NucleoMag Food, and Norgen Stool kits were included. Accession numbersRaw sequence data were deposited at the European Nucleotide Archive (accession#: ERP124610) and raw and processed data are available at Qiita (Study ID: 12201). All processing and analysis code is available on GitHub (github.com/justinshaffer/Extraction_kit_testing). Methods summaryTo allow for downstream applications involving fungi in addition to bacteria and archaea, we compared five DNA extraction kits with our previously established, standardized protocol for extracting DNA for microbial community analysis. Across ten diverse sample types, we found one extraction kit to perform comparably or better than our standardized protocol. Our conclusion is based on per-sample comparisons of DNA yield, the number of quality-filtered sequences generated, the limit of detection of microbial cells, microbial community alpha-diversity, beta-diversity, and taxonomic composition, and extent of well-to-well contamination.

microbiology↗

bioRxiv2022

Multi-omic analysis along the gut-brain axis points to a functional architecture of autism

Autism is a highly heritable neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in autism, with dozens of cross-sectional microbiome and other omic studies revealing autism-specific profiles along the GBA albeit with little agreement in composition or magnitude. To explore the functional architecture of autism, we developed an age and sex-matched Bayesian differential ranking algorithm that identified autism-specific profiles across 10 cross-sectional microbiome datasets and 15 other omic datasets, including dietary patterns, metabolomics, cytokine profiles, and human brain expression profiles. The analysis uncovered a highly significant, functional architecture along the GBA that encapsulated the overall heterogeneity of autism phenotypes. This architecture was determined by autism-specific amino acid, carbohydrate and lipid metabolism profiles predominantly encoded by microbial species in the genera Prevotella, Enterococcus, Bifidobacterium, and Desulfovibrio, and was mirrored in brain-associated gene expression profiles and restrictive dietary patterns in individuals with autism. Pro-inflammatory cytokine profiling and virome association analysis further supported the existence of an autism-specific architecture associated with particular microbial genera. Re-analysis of a longitudinal intervention study in autism recapitulated the cross-sectional profiles, and showed a strong association between temporal changes in microbiome composition and autism symptoms. Further elucidation of the functional architecture of autism, including of the role the microbiome plays in it, will require deep, multi-omic longitudinal intervention studies on well-defined stratified cohorts to support causal and mechanistic inference.

microbiology↗

bioRxiv2022

Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations

Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.

microbiology↗

bioRxiv2022

Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings

Accurate, high-resolution environmental monitoring of SARS-CoV-2 traces indoors through sentinel cards is a promising approach to help students safely return to in-person learning. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface types, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution, but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, wet wipes, RNase Away) at three different viral loads: "high" (4 x 104 GE/mL), "medium" (1 x 104 GE/mL), and "low" (2.5 x 103 GE/mL). RNAse Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. ImportanceBecause SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are persistent signal or new infectious cases, and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning "sentinel cards" to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.

bioinformatics↗

bioRxiv2021

Intestinal Transgene Delivery with Native E. coli Chassis Allows Persistent Physiological Changes

Live bacterial therapeutics (LBT) could reverse disease by engrafting in the gut and providing persistent beneficial functions in the host. However, attempts to functionally manipulate the gut microbiome of conventionally-raised (CR) hosts have been unsuccessful, because engineered microbial organisms (i.e., chassis) cannot colonize the hostile luminal environment. In this proof-of-concept study, we use native bacteria as chassis for transgene delivery to impact CR host physiology. Native Escherichia coli isolated from stool cultures of CR mice were modified to express functional bacterial (bile salt hydrolase) and eukaryotic (Interleukin-10) genes. Reintroduction of these strains induces perpetual engraftment in the intestine. In addition, engineered native E. coli can induce functional changes that affect host physiology and reverse pathology in CR hosts months after administration. Thus, using native bacteria as chassis to "knock-in" specific functions allows mechanistic studies of specific microbial activities in the microbiome of CR hosts, and enables LBT with curative intent.

synthetic biology↗

bioRxiv2021

Kernel-based genetic association analysis for microbiome phenotypes identifies host genetic drivers of beta-diversity

Understanding human genetic influences on the gut microbiota helps elucidate the mechanisms by which genetics affects health outcomes. We propose a novel approach, the covariate-adjusted kernel RV (KRV) framework, to map genetic variants associated with microbiome beta-diversity, which focuses on overall shifts in the microbiota. The proposed KRV framework improves statistical power by capturing intrinsic structure within the genetic and microbiome data while reducing the multiple-testing burden. We apply the covariate-adjusted KRV test to the Hispanic Community Health Study/Study of Latinos in a genome-wide association analysis (first gene-level, then variant-level) for microbiome beta-diversity. We have identified an immunity-related gene, IL23R, reported in previous association studies and discovered 3 other novel genes, 2 of which are involved in immune functions or autoimmune disorders. Our findings highlight the value of the KRV as a powerful microbiome GWAS approach and support an important role of immunity-related genes in shaping the gut microbiome composition.

genomics↗

bioRxiv2021

Context-aware deconvolution of cell-cell communication with Tensor-cell2cell

Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which is the first strategy to decipher context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand receptor pairs) linked to COVID-19 severities and Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.

bioinformatics↗

bioRxiv2021

Engineered bacteria detect tumor DNA in vivo

Advances in bacterial engineering have catalysed the development of living cell diagnostics and therapeutics1-3, including microbes that respond to gut inflammation4, intestinal bleeding5, pathogens6 and hypoxic tumors7. Bacteria can access the entire gastrointestinal tract8 to produce outputs measured in stool4 or urine7. Cellular memory, such as bistable switches4,9,10 or genomic rearrangements11, allows bacteria to store information over time. However, living biosensors have not yet been engineered to detect specific DNA sequences or mutations from outside the cell. Here, we engineer naturally competent Acinetobacter baylyi to detect donor DNA from the genomes of colorectal cancer (CRC) cells, organoids and tumors. We characterize the functionality of the biosensors in vitro with co-culture assays and then validate in vivo with sensor bacteria delivered to mice harboring colorectal tumors. We observe horizontal gene transfer from the tumor to the sensor bacteria in our mouse model of CRC. The sensor bacteria achieved 100% discrimination between mice with and without CRC. This Cellular Assay of Targeted, CRISPR-discriminated Horizontal gene transfer (CATCH), establishes a framework for biosensing of mutations or organisms within environments that are difficult to sample, among many other potential applications. Furthermore, the platform could be readily expanded to include production and delivery of antibiotic or antineoplastic therapeutic payloads at the detection site.

synthetic biology↗

bioRxiv2021

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. ImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

microbiology↗

bioRxiv2021

Targeted Neuronal Activation of the Gastrointestinal Tract Shapes the Environment of the Gut in Mice

The gastrointestinal (GI) tract is extensively innervated by intrinsic neurons of the enteric nervous system (ENS) and extrinsic neurons of the central nervous system and peripheral ganglia, which together regulate gut physiology. The GI tract also harbors a diverse microbiome, but interactions between the ENS and the microbiome remain poorly understood. Herein, we activate choline acetyltransferase (ChAT)-expressing or tyrosine hydroxylase (TH)-expressing gut-associated neurons in mice to determine effects on intestinal microbial communities and their metabolites, as well as on host physiology. The resulting multi-omics datasets support broad roles for discrete peripheral neuronal subtypes in shaping microbiome structure, including modulating bile acid profiles and fungal colonization. Physiologically, activation of either ChAT+ or TH+ neurons increases fecal output, while only ChAT+ activation results in increased colonic migrating motor complexes and diarrhea-like fluid secretion. These findings suggest that specific subsets of peripherally-activated ENS neurons differentially regulate the gut microbiome and GI physiology in mice, without involvement of signals from the brain.

physiology↗

bioRxiv2021

OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies. ImportanceShotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA amplicon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies.

bioinformatics↗

bioRxiv2021

Probiotic bacteria and bile acid profile are modulated by prebiotic diet and associate with facilitated diurnal clock/sleep realignment after chronic disruption of rhythms

Chronic disruption of rhythms (CDR) impacts sleep and can result in circadian misalignment of physiological systems, which in turn is associated with increased disease risk. Exposure to repeated or severe stressors also disturbs sleep and diurnal rhythms. Prebiotic nutrients produce favorable changes in gut microbial ecology, the gut metabolome, and reduce several negative impacts of acute severe stressor exposure, including disturbed sleep, core body temperature rhythmicity, and gut microbial dysbiosis. This study tested the hypothesis whether prebiotics can also reduce the negative impacts of CDR by facilitating light/dark realignment of sleep/wake, core body temperature, and locomotor activity; and whether prebiotic-induced changes in bacteria and bile acid profiles are associated with these effects. Male, Sprague Dawley rats were fed diets enriched in prebiotic substrates or calorically matched control chow. After 5 weeks on diet, rats were exposed to CDR (12h light/dark reversal, weekly for 8 weeks) or remained on undisturbed normal light/dark cycles (NLD). Sleep EEG, core body temperature, and locomotor activity were recorded via biotelemetry in freely moving rats. Fecal samples were collected on experimental days -33, 0 (day of onset of CDR), and 42. Taxonomic identification and relative abundances of gut microbes were measured in fecal samples using 16S rRNA gene sequencing and shotgun metagenomics. Fecal primary, bacterially-modified secondary, and conjugated bile acids were measured using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Prebiotic diet produced rapid and stable increases in the relative abundances of Parabacteroides distasonis and Ruminiclostridium 5. Shotgun metagenomics analyses confirmed reliable increases in relative abundances of Parabacteroides distasonis and Clostridium leptum, a member of the Ruminiclostridium genus. Prebiotic diet also modified fecal bile acid profiles; and based on correlational and step-wise regression analyses, Parabacteroides distasonis and Ruminiclostridium 5 were positively associated with each other and negatively associated with secondary and conjugated bile acids. Prebiotic diet, but not CDR, impacted beta diversity. Measures of alpha diversity evenness were decreased by CDR and prebiotic diet prevented that effect. Rats exposed to CDR while eating prebiotic, compared to control diet, more quickly realigned NREM sleep and core body temperature (ClockLab) diurnal rhythms to the altered light/dark cycle. Finally, both cholic acid and Ruminiclostridium 5 prior to CDR were associated with time to realign CBT rhythms to the new light/dark cycle after CDR; whereas both Ruminiclostridium 5 and taurocholic acid prior to CDR were associated with NREM sleep recovery after CDR. These results suggest that ingestion of prebiotic substrates is an effective strategy to increase the relative abundance of health promoting microbes, alter the fecal bile acid profile, and facilitate the recovery and realignment of sleep and diurnal rhythms after circadian disruption.

physiology↗

bioRxiv2020

Challenges in Benchmarking Metagenomic Profilers

Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classifying metagenomic data and estimating taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Yet, benchmarking metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here, we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community should pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that was analyzed and interpreted, and clearly stating the strategy used for metagenomic profiling.

bioinformatics↗

bioRxiv2020

A comparison of DNA/RNA extraction protocols for high-throughput sequencing of microbial communities

One goal among microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods we previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, we compare the relative performance of two total nucleic acid extraction protocols and our previously benchmarked protocol. We included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here we present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection, and well-to-well contamination, between these protocols. Accession numbersRaw sequence data were deposited at the European Nucleotide Archive (accession#: ERP124610) and raw and processed data are available at Qiita (Study ID: 12201). All processing and analysis code is available on GitHub (github.com/justinshaffer/Extraction_test_MagMAX). Methods summaryTo allow for downstream applications involving RNA-based organisms such as SARS-CoV-2, we compared the two extraction protocols designed to extract DNA and RNA against our previously established protocol for extracting only DNA for microbial community analyses. Across 10 diverse sample types, one of the two protocols was equivalent or better than our established DNA-based protocol. Our conclusion is based on per-sample comparisons of DNA and RNA yield, the number of quality sequences generated, microbial community alpha- and beta-diversity and taxonomic composition, the limit of detection, and extent of well-to-well contamination.

ecology↗

bioRxiv2020

A scale-free, fully connected global transition network underlies known microbiome diversity

Microbiomes are inherently linked by their structural similarity, yet the global features of such similarity are not clear. Here we propose as solution a search-based microbiome transition network. By traversing a composition-similarity based network of 177,022 microbiomes, we show that although the compositions are distinct by habitat, each microbiome is on-average only seven neighbors from any other microbiome on Earth, indicating the inherent homology of microbiome at the global scale. This network is scale-free, suggesting a high degree of stability and robustness in microbiome transition. By tracking the minimum spanning tree in this network, a global roadmap of microbiome dispersal was derived that tracks the potential paths of formulating and propagating microbiome diversity. Such search-based global microbiome networks, reconstructed within hours on just one computing node, provide a readily expanded reference for tracing the origin and evolution of existing or new microbiomes.

microbiology↗

bioRxiv2020

EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic datasets

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive tool for visualizing trees in the context of microbiome, metabolome, etc. community data scalable beyond modern large datasets like the Earth Microbiome Project. EMPress provides novel functionality--including ordination integration and animations--alongside many standard tree visualization features, and thus simplifies exploratory analyses of many forms of omic data.

bioinformatics↗

bioRxiv2020

Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity

The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro, bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/238444v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@14ff1ecorg.highwire.dtl.DTLVardef@193d84corg.highwire.dtl.DTLVardef@15d6f9eorg.highwire.dtl.DTLVardef@14b16c6_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract. Diagram of hypothesis for bacterial mediation of SARS-CoV-2 infection through heparan sulfate (HS).It is well known that host microbes groom the mucosa where they reside. Recent investigations have shown that HS, a major component of mucosal layers, is necessary for SARS-CoV-2 infection. In this study we examine the impact of microbial modification of HS on viral attachment. C_FIG

microbiology↗