Surface colonization by Flavobacterium johnsoniae promotes its survival in a model microbial community

Flavobacterium johnsoniae is a ubiquitous soil and rhizosphere bacterium, but despite its abundance, the factors contributing to its success in communities are poorly understood. Using a model microbial community, The Hitchhikers of the Rhizosphere (THOR), we determined the effects of colonization on the fitness of F. johnsoniae in the community. Insertion sequencing, a massively parallel transposon mutant screen, on sterile sand identified 25 genes likely to be important for surface colonization. We constructed in-frame deletions of candidate genes predicted to be involved in cell membrane biogenesis, motility, signal transduction, and transport of amino acids and lipids. All mutants poorly colonized sand, glass, and polystyrene and produced less biofilm than the wild type, indicating the importance of the targeted genes in surface colonization. Eight of the nine colonization-defective mutants were also unable to form motile biofilms or zorbs, thereby suggesting that the affected genes play a role in group movement and linking stationary and motile biofilm formation genetically. Furthermore, we showed that the deletion of colonization genes in F. johnsoniae affected its behavior and survival in THOR on surfaces, suggesting that the same traits are required for success in a multispecies microbial community. Our results provide insight into the mechanisms of surface colonization by F. johnsoniae and form the basis for further understanding its ecology in the rhizosphere.

IMPORTANCE

Microbial communities direct key environmental processes through multispecies interactions. Understanding these interactions is vital for manipulating microbiomes to promote health in human, environmental, and agricultural systems. However, microbiome complexity can hinder our understanding of the underlying mechanisms in microbial community interactions. As a first step toward unraveling these interactions, we explored the role of surface colonization in microbial community interactions using The Hitchhikers Of the Rhizosphere (THOR), a genetically tractable model community of three bacterial species, Flavobacterium johnsoniae, Pseudomonas koreensis, and Bacillus cereus. We identified F. johnsoniae genes important for surface colonization in solitary conditions and in the THOR community. Understanding the mechanisms that promote the success of bacteria in microbial communities brings us closer to targeted manipulations to achieve outcomes that benefit agriculture, the environment, and human health.

Improved performance of nucleic acid-based assays for genetically diverse norovirus surveillance

Nucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of their genetic diversity. Here, we calculated the variability of nucleotides within the genomes of 10 human viral species in silico and found that endemic viruses exhibit a high percentage of variable nucleotides (e.g., 51.4% for norovirus genogroup II). This genetic diversity led to the variable probability of detection of PCR assays (the proportion of viral sequences that contain the assay's target sequences divided by the total number of viral sequences). We then experimentally confirmed that the probability of the target sequence detection is indicative of the number of mismatches between PCR assays and norovirus genomes. Next, we developed a degenerate PCR assay that detects 97% of known norovirus genogroup II genome sequences and recognized norovirus in eight clinical samples. By contrast, previously developed assays with 31% and 16% probability of detection had 1.1 and 2.5 mismatches on average, respectively, which negatively impacted RNA quantification. In addition, the two PCR assays with a lower probability of detection also resulted in false negatives for wastewater-based epidemiology. Our findings suggest that the probability of detection serves as a simple metric for evaluating nucleic acid-based assays for genetically diverse virus surveillance.IMPORTANCENucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are employed widely as a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of the rapid evolution and genetic variation of viruses. The study analyzed clinical and wastewater samples using multiple PCR assays and found significant performance variation among the PCR assays for genetically diverse norovirus surveillance. This finding suggests that some PCR assays may miss detecting certain virus strains, leading to a compromise in detection sensitivity. To address this issue, we propose a metric called the probability of detection, which can be simply calculated in silico using a code developed in this study, to evaluate nucleic acid-based assays for genetically diverse virus surveillance. This new approach can help improve the sensitivity and accuracy of virus detection, which is crucial for effective infectious disease surveillance and control.

Reconnaissance of Oxygenic Denitrifiers in Agriculturally Impacted Soils

Row crop production in the agricultural Midwest pollutes waterways with nitrate, and exacerbates climate change through increased emissions of nitrous oxide and methane. Oxygenic denitrification processes in agricultural soils mitigate nitrate and nitrous oxide pollution by short-circuiting the canonical pathway to avoid nitrous oxide formation. Furthermore, many oxygenic denitrifiers employ a nitric oxide dismutase (nod) to create molecular oxygen that is used by methane monooxygenase to oxidize methane in otherwise anoxic soils. The direct investigation of nod genes that could facilitate oxygenic denitrification processes in agricultural sites is limited, with no prior studies investigating nod genes at tile drainage sites. Thus, we performed a reconnaissance of nod genes at variably saturated surface sites, and within a variably to fully saturated soil core in Iowa to expand the known distribution of oxygenic denitrifiers. We identified new nod gene sequences from agricultural soil and freshwater sediments in addition to identifying nitric oxide reductase (qNor) related sequences. Surface and variably saturated core samples displayed a nod to 16S rRNA gene relative abundance of 0.004% to 0.1% and fully saturated core samples had relative nod gene abundance of 1.2%. The relative abundance of the phylum Methylomirabilota increased from 0.6% and 1% in the variably saturated core samples to 3.8% and 5.3% in the fully saturated core samples. The more than 10-fold increase in relative nod abundance and almost 9-fold increase in relative Methylomirabilota abundance in fully saturated soils suggests that potential oxygenic denitrifiers play a greater nitrogen cycling role under these conditions. IMPORTANCE The direct investigation of nod genes in agricultural sites is limited, with no prior studies investigating nod genes at tile drains. An improved understanding of nod gene diversity and distribution is significant to the field of bioremediation and ecosystem services. The expansion of the nod gene database will advance oxygenic denitrification as a potential strategy for sustainable nitrate and nitrous oxide mitigation, specifically for agricultural sites.

Estimating the benefits of stream water quality improvements in urbanizing watersheds: An ecological production function approach

Streams in urbanizing watersheds are threatened by economic development that can lead to excessive sediment erosion and surface runoff. These anthropogenic stressors diminish valuable ecosystem services and result in pervasive degradation commonly referred to as "urban stream syndrome." Understanding how the public perceives and values improvements in stream conditions is necessary to support efforts to quantify the economic benefits of water quality improvements. We develop an ecological production framework that translates measurable indicators of stream water quality into ecological endpoints. Our interdisciplinary approach integrates a predictive hierarchical water quality model that is well suited for sparse data environments, an expert elicitation that translates measurable water quality indicators into ecological endpoints that focus group participants identified as most relevant, and a stated preference survey that elicits the public's willingness to pay for changes in these endpoints. To illustrate our methods, we develop an application to the Upper Neuse River Watershed located in the rapidly developing Triangle region of North Carolina (the United States). Our results suggest, for example, that residents are willing to pay roughly $127 per household and $54 million per year in aggregate (2021 US$) for water quality improvements resulting from a stylized intervention that increases stream bank canopy cover by 25% and decreases runoff from impervious surfaces, leading to improvements in water quality and ecological endpoints for local streams. Although the three components of our analysis are conducted with data from North Carolina, we discuss how our findings are generalizable to urban and urbanizing areas across the larger Piedmont ecoregion of the Eastern United States.

Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia

Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks. We developed a computational program, ssCRISPR, which designs strain-specific CRISPR guide RNA sequences with user-specified target strains, protected strains, and guide RNA properties. We experimentally verify the accuracy of the strain specificity predictions in both Escherichia coli and Pseudomonas spp. and show that up to three nucleotide mismatches are often required to ensure perfect specificity. To demonstrate the functionality of ssCRISPR, we apply computationally designed CRISPR-Cas9 guide RNAs to two applications: the purification of specific microbes through one- and two-plasmid transformation workflows and the targeted removal of specific microbes using DNA-loaded liposomes. For strain purification, we utilize gRNAs designed to target and kill all microbes in a consortium except the specific microbe to be isolated. For strain elimination, we utilize gRNAs designed to target only the unwanted microbe while protecting all other strains in the community. ssCRISPR will be of use in diverse microbiota engineering applications.

Sodalis ligni Strain 159R Isolated from an Anaerobic Lignin-Degrading Consortium

Novel bacterial isolates with the capabilities of lignin depolymerization, catabolism, or both, could be pertinent to lignocellulosic biofuel applications. In this study, we aimed to identify anaerobic bacteria that could address the economic challenges faced with microbial-mediated biotechnologies, such as the need for aeration and mixing. Using a consortium seeded from temperate forest soil and enriched under anoxic conditions with organosolv lignin as the sole carbon source, we successfully isolated a novel bacterium, designated 159R. Based on the 16S rRNA gene, the isolate belongs to the genus Sodalis in the family Bruguierivoracaceae. Whole-genome sequencing revealed a genome size of 6.38 Mbp and a GC content of 55 mol%. To resolve the phylogenetic position of 159R, its phylogeny was reconstructed using (i) 16S rRNA genes of its closest relatives, (ii) multilocus sequence analysis (MLSA) of 100 genes, (iii) 49 clusters of orthologous groups (COG) domains, and (iv) 400 conserved proteins. Isolate 159R was closely related to the deadwood associated Sodalis guild rather than the tsetse fly and other insect endosymbiont guilds. Estimated genome-sequence-based digital DNA-DNA hybridization (dDDH), genome percentage of conserved proteins (POCP), and an alignment analysis between 159R and the Sodalis clade species further supported that isolate 159R was part of the Sodalis genus and a strain of Sodalis ligni. We proposed the name Sodalis ligni str. 159R (=DSM 110549 = ATCC TSD-177). IMPORTANCE Currently, in the paper industry, paper mill pulping relies on unsustainable and costly processes to remove lignin from lignocellulosic material. A greener approach is biopulping, which uses microbes and their enzymes to break down lignin. However, there are limitations to biopulping that prevent it from outcompeting other pulping processes, such as requiring constant aeration and mixing. Anaerobic bacteria are a promising alternative source for consolidated depolymerization of lignin and its conversion to valuable by-products. We presented Sodalis ligni str. 159R and its characteristics as another example of potential mechanisms that can be developed for lignocellulosic applications.

Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction

MOTIVATION

Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a highly reproducible metric for feature annotation, the collision cross-section (CCS).

RESULTS

We present a data processing workflow to increase confidence in molecular class annotations based on CCS values. This approach uses class-specific regression models built from a standardized CCS repository (the Unified CCS Compendium) in a parallel scheme that combines a new annotation filtering approach with a machine learning class prediction strategy. In a proof-of-concept study using murine brain lipid extracts, 883 lipids were assigned higher confidence identifications using the filtering approach, which reduced the tentative candidate lists by over 50% on average. An additional 192 unannotated compounds were assigned a predicted chemical class.

AVAILABILITY AND IMPLEMENTATION

All relevant source code is available at https://github.com/McLeanResearchGroup/CCS-filter.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SARS-CoV-2 Seroprevalence among a Southern U.S. Population Indicates Limited Asymptomatic Spread under Physical Distancing Measures

Characterizing the asymptomatic spread of SARS-CoV-2 is important for understanding the COVID-19 pandemic. This study was aimed at determining asymptomatic spread of SARS-CoV-2 in a suburban, Southern U.S. population during a period of state restrictions and physical distancing mandates. This is one of the first published seroprevalence studies from North Carolina and included multicenter, primary care, and emergency care facilities serving a low-density, suburban and rural population since description of the North Carolina state index case introducing the SARS-CoV-2 respiratory pathogen to this population. To estimate point seroprevalence of SARS-CoV-2 among asymptomatic individuals over time, two cohort studies were examined. The first cohort study, named ScreenNC, was comprised of outpatient clinics, and the second cohort study, named ScreenNC2, was comprised of inpatients unrelated to COVID-19. Asymptomatic infection by SARS-CoV-2 (with no clinical symptoms) was examined using an Emergency Use Authorization (EUA)-approved antibody test (Abbott) for the presence of SARS-CoV-2 IgG. This assay as performed under CLIA had a reported specificity/sensitivity of 100%/99.6%. ScreenNC identified 24 out of 2,973 (0.8%) positive individuals among asymptomatic participants accessing health care during 28 April to 19 June 2020, which was increasing over time. A separate cohort, ScreenNC2, sampled from 3 March to 4 June 2020, identified 10 out of 1,449 (0.7%) positive participants.IMPORTANCE This study suggests limited but accelerating asymptomatic spread of SARS-CoV-2. Asymptomatic infections, like symptomatic infections, disproportionately affected vulnerable communities in this population, and seroprevalence was higher in African American participants than in White participants. The low, overall prevalence may reflect the success of shelter-in-place mandates at the time this study was performed and of maintaining effective physical distancing practices among suburban populations. Under these public health measures and aggressive case finding, outbreak clusters did not spread into the general population.

Elucidating Syntrophic Butyrate-Degrading Populations in Anaerobic Digesters Using Stable-Isotope-Informed Genome-Resolved Metagenomics

Linking the genomic content of uncultivated microbes to their metabolic functions remains a critical challenge in microbial ecology. Resolving this challenge has implications for improving our management of key microbial interactions in biotechnologies such as anaerobic digestion, which relies on slow-growing syntrophic and methanogenic communities to produce renewable methane from organic waste. In this study, we combined DNA stable-isotope probing (SIP) with genome-centric metagenomics to recover the genomes of populations enriched in 13C after growing on [13C]butyrate. Differential abundance analysis of recovered genomic bins across the SIP metagenomes identified two metagenome-assembled genomes (MAGs) that were significantly enriched in heavy [13C]DNA. Phylogenomic analysis assigned one MAG to the genus Syntrophomonas and the other MAG to the genus Methanothrix. Metabolic reconstruction of the annotated genomes showed that the Syntrophomonas genome encoded all the enzymes for beta-oxidizing butyrate, as well as several mechanisms for interspecies electron transfer via electron transfer flavoproteins, hydrogenases, and formate dehydrogenases. The Syntrophomonas genome shared low average nucleotide identity (<95%) with any cultured representative species, indicating that it is a novel species that plays a significant role in syntrophic butyrate degradation within anaerobic digesters. The Methanothrix genome contained the complete pathway for acetoclastic methanogenesis, indicating that it was enriched in 13C from syntrophic acetate transfer. This study demonstrates the potential of stable-isotope-informed genome-resolved metagenomics to identify in situ interspecies metabolic cooperation within syntrophic consortia important to anaerobic waste treatment as well as global carbon cycling.IMPORTANCE Predicting the metabolic potential and ecophysiology of mixed microbial communities remains a major challenge, especially for slow-growing anaerobes that are difficult to isolate. Unraveling the in situ metabolic activities of uncultured species may enable a more descriptive framework to model substrate transformations by microbiomes, which has broad implications for advancing the fields of biotechnology, global biogeochemistry, and human health. Here, we investigated the in situ function of mixed microbiomes by combining stable-isotope probing with metagenomics to identify the genomes of active syntrophic populations converting butyrate, a C4 fatty acid, into methane within anaerobic digesters. This approach thus moves beyond the mere presence of metabolic genes to resolve "who is doing what" by obtaining confirmatory assimilation of the labeled substrate into the DNA signature. Our findings provide a framework to further link the genomic identities of uncultured microbes with their ecological function within microbiomes driving many important biotechnological and global processes.

Inactivation of Pseudomonas aeruginosa and Methicillin-resistant Staphylococcus aureus in an open water system with ozone generated by a compact, atmospheric DBD plasma reactor

Ozone is a well-known disinfecting agent that is used as an alternative for chlorine in many applications, including water decontamination. However, the utility of ozone in water decontamination is limited by high electrical power consumption and expensive, bulky equipment associated with ozone generation. This study investigates the effectiveness of a lightweight, compact surface dielectric barrier discharge (SDBD) reactor as an ozone generator to inactivate Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) in an open water system. Experimental details are provided for ozone generation technique, mixing method, ozone concentrations in air and water, and input energy required to produce adequate ozone concentrations for bacterial inactivation in a contaminated, open water system. Specifically, an active plasma module (APM) reactor system of size 48 cubic centimeters, weighing 55 grams, with a maximum ozone yield of 68.6 g/KWh was used in atmospheric conditions as the source of ozone along with an air pump and a diffusion stone for mixing the ozone in water. Over 4-log reduction in P. aeruginosa concentration was achieved in 4 minutes with 0.1 mg/L ozone concentration in an open water system using 8.8 ± 1.48 J input energy. Also, over 5-log reduction in MRSA concentration was achieved in 2 minutes with 0.04 mg/L ozone concentration in an open water system using 4.4 ± 0.74 J input energy.

Potential influence of temperature and precipitation on preterm birth rate in Puerto Rico

The preterm birth (PTB) rate for singletons born in the tropical Caribbean island Puerto Rico increased from 11.3% in 1994, which was comparable to rates in the U.S., to as high as 18.3% in 2006 before decreasing to 15.5% in 2012. A few studies have reported that weather extremes are associated with higher risk of preterm birth, however, the effects of ambient temperature and precipitation has not been well examined in Puerto Rico. We compiled child birth data from the National Center for Health Statistics and weather data from the National Oceanic and Atmospheric Administration from 1994 to 2012. We explored the association between the weather factors and PTB rates with a distributed lag non-linear model (DLNM). We did not find direct association of lagged effect of temperature on birth outcome over monthly timescales. Both high intensity and frequency of precipitation and high frequency of storm and flood events are associated with increased risk of PTB rates. While the weather factors do not explain the marked increase and decrease in PTB rate, we emphasize the negative effects on PTB from weather extremes particularly precipitation in Puerto Rico.

Sex-specific associations of infants' gut microbiome with arsenic exposure in a US population

Arsenic is a ubiquitous environmental toxicant with antimicrobial properties that can be found in food and drinking water. The influence of arsenic exposure on the composition of the human microbiome in US populations remains unknown, particularly during the vulnerable infant period. We investigated the relationship between arsenic exposure and gut microbiome composition in 204 infants prospectively followed as part of the New Hampshire Birth Cohort Study. Infant urine was analyzed for total arsenic concentration using inductively coupled plasma mass spectrometry. Stool microbiome composition was determined using sequencing of the bacterial 16S rRNA gene. Infant urinary arsenic related to gut microbiome composition at 6 weeks of life (p = 0.05, adjusted for infant feeding type and urine specific gravity). Eight genera, six within the phylum Firmicutes, were enriched with higher arsenic exposure. Fifteen genera were negatively associated with urinary arsenic concentration, including Bacteroides and Bifidobacterium. Upon stratification by both sex and feeding method, we found detectable associations among formula-fed males (p = 0.008), but not other groups (p > 0.05 for formula-fed females and for breastfed males and females). Our findings from a US population indicate that even moderate arsenic exposure may have meaningful, sex-specific effects on the gut microbiome during a critical window of infant development.

Transcriptomic Analysis of Hepatic Cells in Multicellular Organotypic Liver Models

Liver homeostasis requires the presence of both parenchymal and non-parenchymal cells (NPCs). However, systems biology studies of the liver have primarily focused on hepatocytes. Using an organotypic three-dimensional (3D) hepatic culture, we report the first transcriptomic study of liver sinusoidal endothelial cells (LSECs) and Kupffer cells (KCs) cultured with hepatocytes. Through computational pathway and interaction network analyses, we demonstrate that hepatocytes, LSECs and KCs have distinct expression profiles and functional characteristics. Our results show that LSECs in the presence of KCs exhibit decreased expression of focal adhesion kinase (FAK) signaling, a pathway linked to LSEC dedifferentiation. We report the novel result that peroxisome proliferator-activated receptor alpha (PPARα) is transcribed in LSECs. The expression of downstream processes corroborates active PPARα signaling in LSECs. We uncover transcriptional evidence in LSECs for a feedback mechanism between PPARα and farnesoid X-activated receptor (FXR) that maintains bile acid homeostasis; previously, this feedback was known occur only in HepG2 cells. We demonstrate that KCs in 3D liver models display expression patterns consistent with an anti-inflammatory phenotype when compared to monocultures. These results highlight the distinct roles of LSECs and KCs in maintaining liver function and emphasize the need for additional mechanistic studies of NPCs in addition to hepatocytes in liver-mimetic microenvironments.