Metagenomic Sequencing Approach Research Articles

Readsynth: short-read simulation for consideration of composition-biases in reduced metagenome sequencing approaches

BackgroundThe application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates.ResultsThrough the development and application of simulation software, readsynth, we compare simulated metagenomic sequencing libraries with existing RMS data to assess the influence of multiple library preparation and sequencing steps on downstream analytical results. Based on read depth per position, readsynth achieved 0.79 Pearson’s correlation and 0.94 Spearman’s correlation to these benchmarks. Application of a novel estimation approach, fixed length taxonomic ratios, improved quantification accuracy of simulated human gut microbial communities when compared to estimates of mean or median coverage.ConclusionsWe investigate the possible strengths and weaknesses of applying the RMS technique to profiling microbial communities via simulations with readsynth. The choice of restriction enzymes and size selection steps in library prep are non-trivial decisions that bias downstream profiling and quantification. The simulations investigated in this study illustrate the possible limits of preparing metagenomic libraries with a reduced representation sequencing approach, but also allow for the development of strategies for producing and handling the sequence data produced by this promising application.

Perspective: Microbial hydrogen metabolism in rock-hosted ecosystems

Hydrogen (H2) is among the most common and widely utilized electron donors in microbial metabolism. This is particularly true for microorganisms that inhabit subsurface environments where H2 concentrations can be high due to H2 generation via one or more abiotic and biotic processes, such as serpentinization, radiolysis, cataclasis, and microbial fermentation. A surge in interest in the exploration for and exploitation of geologic (i.e., white and orange) H2 as a clean low carbon fuel therefore necessitates an evaluation of the influence of microorganisms on its flux and potential recovery from subsurface systems. The widespread application of high throughput metagenomic sequencing approaches to rock-hosted ecosystems now makes it possible to readily identify microorganisms that harbor the potential to metabolize H2 and to predict their mode of coupling H2 oxidation with available oxidants using comparative genomic data from natural samples alone. When combined with several recent reports of measured rates of net microbial H2 consumption in rock-hosted ecosystems, such information provides new perspective on the potential for microorganisms to impact the economics of H2 recovery from geologic systems. In this perspective, the different classes of enzymes that microorganisms use to reversibly oxidize H2 to fuel their energy metabolism are introduced and their distribution in several rock-hosted ecosystems is discussed. A compilation of net microbial H2 oxidation activities in rock-hosted ecosystems is also presented to enable estimates of potential H2 loss from natural or stimulated geologic reservoirs during mining activities, with an example provided from the Samail Ophiolite that indicates >90% of geologic H2 produced could be lost to microbial consumption. Finally, avenues to guide future microbial research in environments where geologic H2 mining is planned are discussed.

Metagenomic Detection and Genetic Characterization of Human Sapoviruses among Children with Acute Flaccid Paralysis in Nigeria.

Using a metagenomic sequencing approach on stool samples from children with Acute Flaccid Paralysis (AFP), we describe the genetic diversity of Sapoviruses (SaVs) in children in Nigeria. We identified six complete genome sequences and two partial genome sequences. Several SaV genogroups and genotypes were detected, including GII (GII.4 and GII.8), GIV (GIV.1), and GI (GI.2 and GI.7). To our knowledge, this is the first description of SaV infections and complete genomes from Nigeria. Pairwise identity and phylogenetic analysis showed that the Nigerian SaVs were related to previously documented gastroenteritis outbreaks with associated strains from China and Japan. Minor variations in the functional motifs of the nonstructural proteins NS3 and NS5 were seen in the Nigerian strains. To adequately understand the effect of such amino acid changes, a better understanding of the biological function of these proteins is vital. The identification of distinct SaVs reinforces the need for robust surveillance in acute gastroenteritis (AGE) and non-AGE cohorts to better understand SaVs genotype diversity, evolution, and its role in disease burden in Nigeria. Future studies in different populations are, therefore, recommended.

Urbanization-driven forest soil greenhouse gas emissions: Insights from the role of soil bacteria in carbon and nitrogen cycling using a metagenomic approach

Increasing population densities and urban sprawl have induced greenhouse gas (GHG) emissions from the soil, and the soil microbiota of urban forests play a critical role in the production and consumption of GHGs, supporting green development. However, the function and potential mechanism of soil bacteria in GHG emissions from forests during urbanization processes need to be better understood. Here, we measured the fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in Cinnamomum camphora forest soils along an urbanization gradient. 16S amplicon and metagenomic sequencing approaches were employed to examine the structure and potential functions of the soil bacterial community involved in carbon (C) and nitrogen (N) cycling. In this study, the CH4 and CO2 emissions from urban forest soils (sites U and G) were significantly greater than those from suburban soils (sites S and M). The N2O emissions in the urban center (site U) were 24.0 % (G), 13.8 % (S), and 13.5 % (M) greater than those at the other three sites. These results were related to the increasing bacterial alpha diversity, interactions, and C and N cycling gene abundances (especially those involved in denitrification) in urban forest soils. Additionally, the soil pH and metal contents (K, Ca, Mg) affected key bacterial populations (such as Methylomirabilota, Acidobacteriota, and Proteobacteria) and indicators (napA, nosZ, nrfA, nifH) involved in reducing N2O emissions. The soil heavy metal contents (Fe, Cr, Pb) were the main contributors to CH4 emissions, possibly by affecting methanogens (Desulfobacterota) and methanotrophic bacteria (Proteobacteria, Actinobacteriota, and Patescibacteria). Our study provides new insights into the benefits of conservation-minded urban planning and close-to-nature urban forest management and construction, which are conducive to mitigating GHG emissions and supporting urban sustainable development by mediating the core bacterial population.

Metabolic analysis of the CAZy class glycosyltransferases in rhizospheric soil fungiome of the plant species Moringa oleifera

The target of the present work is to study the most abundant carbohydrate-active enzymes (CAZymes) of glycosyltransferase (GT) class, which are encoded by fungiome genes present in the rhizospheric soil of the plant species Moringa oleifera. The datasets of this CAZy class were recovered using metagenomic whole shotgun genome sequencing approach, and the resultant CAZymes were searched against the KEGG pathway database to identify function. High emphasis was given to the two GT families, GT4 and GT2, which were the highest within GT class in the number and abundance of gene queries in this soil compartment. These two GT families harbor CAZymes playing crucial roles in cell membrane and cell wall processes. These CAZymes are responsible for synthesizing essential structural components such as cellulose and chitin, which contribute to the integrity of cell walls in plants and fungi. The CAZyme beta-1,3-glucan synthase of GT2 family accumulates 1,3-β-glucan, which provides elasticity as well as tensile strength to the fungal cell wall. Other GT CAZymes contribute to the biosynthesis of several compounds crucial for cell membrane and wall integrity, including lipopolysaccharide, e.g., lipopolysaccharide N-acetylglucosaminyltransferase, cell wall teichoic acid, e.g., alpha-glucosyltransferase, and cellulose, e.g., cellulose synthase. These compounds also play pivotal roles in ion homeostasis, organic carbon mineralization, and osmoprotection against abiotic stresses in plants. This study emphasizes the major roles of these two CAZy GT families in connecting the structure and function of cell membranes and cell walls of fungal and plant cells. The study also sheds light on the potential occurrence of tripartite symbiotic relationships involving the plant, rhizospheric bacteriome, and fungiome via the action of CAZymes of GT4 and GT2 families. These findings provide valuable insights towards the generation of innovative agricultural practices to enhance the performance of crop plants in the future.

Trichuris trichiura infection is associated with changes in gut microbiome composition and function among women of reproductive age from Pemba, Tanzania

Large intestine-dwelling helminths affect microbiome composition. In sub-Saharan Africa, where helminth infections are endemic, the use of chemotherapeutic drugs is the primary strategy for controlling soil-transmitted helminthiases (STHs). However, the emergence of anthelmintic resistance necessitates the urgent exploration of alternative and complementary treatments to achieve the World Health Organization’s goal of eliminating STHs. One promising avenue involves the manipulation of gut microbiota in at-risk populations. This study aimed to enhance the understanding of the interplay between Trichuris trichiura and the gut microbiome. In this study, we used the Mini-FLOTAC technique for parasitological analyses and a shotgun metagenomic sequencing approach to investigate the effect of T. trichiura on the gut microbiome by comparing infected and non-infected women of reproductive age (WRA) from Pemba. Structural and functional analyses of the gut microbiome revealed that T. trichiura infection shaped the host gut microbiome in WRA. Some taxa vary according to infection status. Prevotella genus was more abundant in healthy participants, whereas species such as Weissella cibaria, Leuconostoc citreum (new emergent probiotics), and Leuconostoc lactis (starter) decreased in infected individuals, suggesting the use of potential probiotic treatments to mitigate dysbiosis induced by STHs. Furthermore, the overall number of common fungi, irrespective of species, was significantly higher in the mycobiome of Trichuris infected participants. Functional analysis revealed significant differences in metabolic pathways (p < 0.05), with cholesterol metabolism and pathogenic infections being more abundant in the infected samples than in the non-infected samples. In conclusion, this study sheds light on the intricate interactions between helminth infections and the gut microbiome in the WRA, particularly in STH-endemic regions. The identified associations between specific gut microbial changes and T. trichiura infection may pave the way for innovative complementary treatments to effectively combat STHs.

Seasonal changes in N-cycling functional genes in sediments and their influencing factors in a typical eutrophic shallow lake, China.

N-cycling processes mediated by microorganisms are directly linked to the eutrophication of lakes and ecosystem health. Exploring the variation and influencing factors of N-cycling-related genes is of great significance for controlling the eutrophication of lakes. However, seasonal dynamics of genomic information encoding nitrogen (N) cycling in sediments of eutrophic lakes have not yet been clearly addressed. We collected sediments in the Baiyangdian (BYD) Lake in four seasons to explore the dynamic variation of N-cycling functional genes based on a shotgun metagenome sequencing approach and to reveal their key influencing factors. Our results showed that dissimilatory nitrate reduction (DNRA), assimilatory nitrate reduction (ANRA), and denitrification were the dominant N-cycling processes, and the abundance of nirS and amoC were higher than other functional genes by at least one order of magnitude. Functional genes, such as nirS, nirK and amoC, generally showed a consistent decreasing trend from the warming season (i.e., spring, summer, fall) to the cold season (i.e., winter). Furthermore, a significantly higher abundance of nitrification functional genes (e.g., amoB, amoC and hao) in spring and denitrification functional genes (e.g., nirS, norC and nosZ) in fall were observed. N-cycling processes in four seasons were influenced by different dominant environmental factors. Generally, dissolved organic carbon (DOC) or sediment organic matter (SOM), water temperature (T) and antibiotics (e.g., Norfloxacin and ofloxacin) were significantly correlated with N-cycling processes. The findings imply that sediment organic carbon and antibiotics may be potentially key factors influencing N-cycling processes in lake ecosystems, which will provide a reference for nitrogen management in eutrophic lakes.

Metagenomic exploration of Andaman region of the Indian Ocean

Ocean microbiome is crucial for global biogeochemical cycles and primary productivity. Despite numerous studies investigating the global ocean microbiomes, the microbiome composition of the Andaman region of the Indian Ocean remains largely unexplored. While this region harbors pristine biological diversity, the escalating anthropogenic activities along coastal habitats exert an influence on the microbial ecology and impact the aquatic ecosystems. We investigated the microbiome composition in the coastal waters of the Andaman Islands by 16S rRNA gene amplicon and metagenomic shotgun sequencing approaches and compared it with the Tara Oceans Consortium. In the coastal waters of the Andaman Islands, a significantly higher abundance and diversity of Synechococcus species was observed with a higher abundance of photosynthesis pigment-related genes to adapt to variable light conditions and nutrition. In contrast, Prochlorococcus species showed higher abundance in open ocean water samples of the Indian Ocean region, with a relatively limited functional diversity. A higher abundance of antibiotic-resistance genes was also noted in the coastal waters region. We also updated the ocean microbiome gene catalog with 93,172 unique genes from the Andaman coastal water microbiome. This study provides valuable insights into the Indian Ocean microbiome and supplements the global marine microbial ecosystem studies.

Depth-dependent microbial metagenomes sampled in the northeastern Indian Ocean

The northeastern Indian Ocean exhibits distinct hydrographic characteristics influenced by various local and remote forces. Variations in these driving factors may alter the physiochemical properties of seawater, such as dissolved oxygen levels, and affect the diversity and function of microbial communities. How the microbial communities change across water depths spanning a dissolved oxygen gradient has not been well understood. Here we employed both 16S rDNA amplicon and metagenomic sequencing approaches to study the microbial communities collected from different water depths along the E87 transect in the northeastern Indian Ocean. Samples were collected from the surface, Deep Chlorophyll Maximum (DCM), Oxygen Minimum Zone (OMZ), and bathypelagic layers. Proteobacteria were prevalent throughout the water columns, while Thermoproteota were found to be abundant in the aphotic layers. A total of 675 non-redundant metagenome-assembled genomes (MAGs) were constructed, spanning 21 bacterial and 5 archaeal phyla. The community structure and genomic information provided by this dataset offer valuable resources for the analysis of microbial biogeography and metabolism in the northeastern Indian Ocean.

Profiling pathogenic protozoan and their functional pathways in wastewater using 18S rRNA and shotgun metagenomics

Despite extensive research, little is known about the composition of eukaryotic protists in environmental samples. This is due to low parasite concentrations, the complexity of parasite diversity, and a lack of suitable reference databases and standardized protocols. To bridge this knowledge gap, this study used 18S rRNA short amplicon and shotgun metagenomic sequencing approaches to profile protozoan microbial communities as well as their functional pathways in treated and untreated wastewater samples collected from different regions of South Africa. Results demonstrated that protozoan diversity (Shannon index P-value = 0.03) and taxonomic composition (PERMANOVA, P-value = 0.02) was mainly driven by the type of wastewater samples (treated & untreated) and geographic location. However, these WWTPs were also found to contain a core community of protozoan parasites. The untreated wastewater samples revealed a predominant presence of free-living, parasitic, and potentially pathogenic protists typically found in humans and animals, ranging from Alveolata (27 %) phylum (Apicomplexa and Ciliophora) to Excavata (3.88 %) (Discoba and Parasalia) and Amoebozoa (2.84 %) (Entamoeba and Acanthamoeba). Shotgun metagenomics analyses in a subset of the untreated wastewater samples confirmed the presence of public health-importance protozoa, including Cryptosporidium species (3.48 %), Entamoeba hystolitica (6.58 %), Blastocystis hominis (2.91 %), Naegleria gruberi (2.37 %), Toxoplasma gondii (1.98 %), Cyclospora cayetanensis (1.30 %), and Giardia intestinalis (0.31 %). Virulent gene families linked to pathogenic protozoa, such as serine/threonine protein phosphatase and mucin-desulfating sulfatase were identified. Additionally, enriched pathways included thiamine diphosphate biosynthesis III, heme biosynthesis, Methylerythritol 4-Phosphate Pathway, methyl erythritol phosphate (MEP), and pentose phosphate pathways. These findings suggest that protozoan pathogens may possess metabolic and growth potential within WWTPs, posing a severe risk of transmission to humans and animals if inadequately disinfected before release. This study provides a baseline for the future investigation of diverse protozoal communities in wastewater, which are of public health importance.

Detection of pathogens from venous or arterial blood of patients with left-sided infective endocarditis by metagenomic next-generation sequencing: A prospective study

BackgroundInfective endocarditis is a life-threatening uncommon infectious disease, and we aimed to explore the clinical utility of venous or arterial blood-based metagenomic next-generation sequencing (mNGS) approaches to diagnose left-sided infective endocarditis (LSIE). MethodsWe prospectively studied 79 LSIE patients who received valvular surgery in our hospital. Results of blood culture, valve culture, venous blood-based mNGS, arterial blood-based mNGS, venous blood-based mNGS plus blood culture, and arterial blood-based mNGS plus blood culture were evaluated and compared. ResultsBoth venous blood- and arterial blood-based mNGS methods displayed significantly higher positive detection rates than blood culture and valve culture (43.0 %, 49.4 % vs. 32.9 %, 19.0 %; P < 0.001). Strikingly, when combining blood-based mNGS and blood culture, the positive rate could be further improved to more than 60 %. Moreover, we found mNGS LSIE detection was closely associated with preoperative leukocyte (P = 0.027), neutrophil value (P = 0.018), vegetation ≥ 14 mm (P = 0.043), and vegetations in aortic valve (P = 0.048). In addition, we discovered that blood-based mNGS had a superir capacity over blood culture to detect gram-negative bacteria, fungi, Bartonella Quintana, and mixed infections than blood culture. ConclusionThis study indicates that venous blood- and arterial blood-based mNGS displayed high positive rate in the rapid detection of pathogens in high-risk LSIE patients.

Multi-site microbiota alteration is a hallmark of kidney stone formation

BackgroundInquiry of microbiota involvement in kidney stone disease (KSD) has largely focussed on potential oxalate handling abilities by gut bacteria and the increased association with antibiotic exposure. By systematically comparing the gut, urinary, and oral microbiota of 83 stone formers (SF) and 30 healthy controls (HC), we provide a unified assessment of the bacterial contribution to KSD.ResultsAmplicon and shotgun metagenomic sequencing approaches were consistent in identifying multi-site microbiota disturbances in SF relative to HC. Biomarker taxa, reduced taxonomic and functional diversity, functional replacement of core bioenergetic pathways with virulence-associated gene markers, and community network collapse defined SF, but differences between cohorts did not extend to oxalate metabolism.ConclusionsWe conclude that multi-site microbiota alteration is a hallmark of SF, and KSD treatment should consider microbial functional restoration and the avoidance of aberrant modulators such as poor diet and antibiotics where applicable to prevent stone recurrence.7-LZNFESG25-7M4uP2eh2iVideo

Pedological factors as drivers of archaeal and fungal communities in maize rhizosphere: a shotgun metagenomic sequencing approach

South Africa is a semi-arid country in need of soil conservation methods for sustainable agroecosystem practices. Over time, researchers have worked extensively on the plant growth beneficial effects of fungi. However, archaeal groups in the soil and rhizosphere of different plants are under-studied. The impact of soil edaphic factors on the community structure of archaeal and fungal groups in the maize rhizosphere is the focus of this research. This will confirm the hypothesis that environmental factors have a significant impact on the plant–soil rhizobiome. To achieve this objective, a shotgun metagenomics approach was used to analyze maize rhizosphere and bulk soils collected from North West and Gauteng provinces of South Africa. Our findings revealed that both the maize rhizosphere and bulk soils have several archaeal and fungal phyla in common. Besides, Ascomycota (30‒51%), Thaumarchaeota (14‒26%), Euryarchaeota (19‒29%), and Crenarchaeota (8‒12%) have significantly dominated the maize rhizosphere and surrounding bulk soils. In comparison, genera such as Nitrosopumilus (Ls-18.32%, Lc-16.25%; Rs-15.45%, Rc-11.47%), Candidatus Nitrososphaera (Ls-15.29%, Lc-13.37%; Rs-10.53%, Rc-8.29%), Cenarchaeum (Ls-8.84%, Lc-8.16%; Rs-7.63%, Rc-5.38%), Chaetomium (Ls-25.15%, Lc-23.05%; Rs-14.83%, Rc-6.29%), and Neurospora (Ls-2.09%, Lc-1.95%; Rs-1.05%, Rc-0.99%) were significantly higher in maize rhizosphere soils compared to bulk soils (p < 0.05). Diversity indices showed that the archaeal and fungal composition were significantly different across samples with the presence of unclassified groups that could indicate the possibility of novel organisms in the sampling areas. The forward selection of soil edaphic factors predicted N–NH4, pH, and organic matter as the major contributing factors to the variation in the fungal and archaeal communities. To fully exploit the advantages possessed by these species, it is necessary to better understand the main environmental factors driving microbial assemblages of the soil microbiome. In addition, mapping out a culture-based method to unveil the unclassified groups could assist in the discovery of biotechnologically important archaeal and fungal groups for sustainable plant growth.

Eukaryotic genomes from a global metagenomic data set illuminate trophic modes and biogeography of ocean plankton.

Metagenomics is a powerful method for interpreting the ecological roles and physiological capabilities of mixed microbial communities. Yet, many tools for processing metagenomic data are neither designed to consider eukaryotes nor are they built for an increasing amount of sequence data. EukHeist is an automated pipeline to retrieve eukaryotic and prokaryotic metagenome-assembled genomes (MAGs) from large-scale metagenomic sequence data sets. We developed the EukHeist workflow to specifically process large amounts of both metagenomic and/or metatranscriptomic sequence data in an automated and reproducible fashion. Here, we applied EukHeist to the large-size fraction data (0.8-2,000 µm) from Tara Oceans to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of >900 environmentally relevant eukaryotic MAGs and >4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs expand upon the phylogenetic diversity of likely particle- and host-associated taxa. We use these MAGs to demonstrate an approach to infer the putative trophic mode of the recovered eukaryotic MAGs. We also identify ecological cohorts of co-occurring MAGs, which are driven by specific environmental factors and putative host-microbe associations. These data together add to a number of growing resources of environmentally relevant eukaryotic genomic information. Complementary and expanded databases of MAGs, such as those provided through scalable pipelines like EukHeist, stand to advance our understanding of eukaryotic diversity through increased coverage of genomic representatives across the tree of life.IMPORTANCESingle-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers' efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity.

Direct Dengue Virus Genome Sequencing from Antigen NS1 Rapid Diagnostic Tests: A Proof-of-Concept with the Standard Q Dengue Duo Assay.

With nearly half of the world's population being at risk of infection, dengue virus represents a major global health issue. The use of dengue antigen rapid diagnostic tests (Ag-RDTs) represents an alternative to PCR methods for the diagnosis of acute infections since they display excellent sensitivities and specificities and can be performed outside the laboratory. The high genetic diversity of the dengue virus genome represents a challenge for vaccine development, and the progressive expansion of this virus into previously nonendemic regions justifies the implementation of a genomic surveillance program. In this proof-of-concept study, we show the feasibility of sequencing dengue virus genomes directly from positive Ag-RDT (Standard Q Dengue Duo Test assay, n = 7) cassettes stored up to 31 days at room temperature after testing. For 5 of the 7 samples, a high number of reads were obtained allowing phylogenetic analyses to be carried out to determine not only the serotypes (dengue 1, 2, 3 and 4 were detected) but also the genotypes. Furthermore, in one sample, our unbiased metagenomic next-generation sequencing approach made it possible to detect epizootic hemorrhagic disease virus sequences, an arthropod-transmitted virus in ruminants. To conclude, as such an approach requires no cold storage or freezing of samples, dengue Ag-RDTs represent a very pragmatic and robust alternative for the genomic surveillance of dengue virus.

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities.

Microorganisms frequently colonize surfaces within food production facilities. Detection of Listeria monocytogenes in this setting relies on culture-dependent methods, but the complex dynamics of bacterial interactions within these environments and their impact on pathogen detection remain largely unexplored. To address this challenge, we applied both 16S rRNA and shotgun quasimetagenomic (enriched microbiome) sequencing of swab culture enrichments from five seafood and seven dairy production environments. Utilizing 16S rRNA amplicon sequencing, we observed variability between 355 samples taken from these 12 production facilities and a distinctive microbiome for each environment. With shotgun quasimetagenomic sequencing, we were able to assemble L. monocytogenes metagenome-assembled genomes (MAGs) from 28 of the 32 culture-positive samples. We compared these MAGs to their corresponding whole-genome sequencing assemblies, which resulted in two polyphyletic clades consisting of L. monocytogenes lineages I and II with 13,195 and 25,556 single-nucleotide polymorphism sites, respectively. The remaining four MAGs did not produce sufficient genome coverage. To understand and establish limits for pathogen detection and subtyping using shotgun quasimetagenomics, these same data sets were downsampled in slilico to produce a titration series of abundances of L. monocytogenes and analyzed. Pathogen detection was achieved for all downsampled data sets, even those with only 3× genome coverage. This study contributes to the understanding of microbial diversity within food production environments and presents insights into the level of genome coverage needed in a metagenome sequencing data set to detect, subtype, and source track a foodborne pathogenIMPORTANCEIn developed countries, the human diet is predominated by food commodities, which have been manufactured, processed, and stored in a food production facility. Little is known about the application of metagenomic sequencing approaches for detecting foodborne pathogens, such as L. monocytogenes, and characterizing microbial diversity in food production ecosystems. In this work, we investigated the utility of 16S rRNA amplicon and quasimetagenomic sequencing for the taxonomic and phylogenetic classification of Listeria culture enrichments of environmental swabs collected from dairy and seafood production facilities. We demonstrated that single-nucleotide polymorphism (SNP) analyses of L. monocytogenes metagenome-assembled genomes (MAGs) from quasimetagenomic data sets can achieve similar resolution as culture isolate whole-genome sequencing. To further understand the impact of genome coverage on MAG SNP cluster resolution, an in silico downsampling approach was employed to reduce the percentage of target pathogen sequence reads, providing an initial estimate of required MAG coverage for subtyping resolution of L. monocytogenes.

Acid tolerance of lactate-utilizing bacteria of the order Bacteroidales contributes to prevention of ruminal acidosis in goats adapted to a high-concentrate diet.

The rapid accumulation of organic acids, particularly lactate, has been suggested as the main cause of ruminal acidosis (RA) for ruminants fed high-concentrate diets. Previous research has shown that a gradual shift from low-to high-concentrate diets within 4 to 5 weeks effectively reduces the risk for RA. However, the mechanisms remain unknown. In this study, 20 goats were randomly allocated into four groups (n=5) and fed with a diet containing a weekly increasing concentrate portion of 20%, 40%, 60%, and 80% over 28d. At d 7, 14, 21, and 28, one group (named C20, C40, C60, and C80 according to the last concentrate level that they received) was killed and the ruminal microbiome was collected. Ruminal acidosis was not detected in any of the goats during the experiment. Nonetheless, ruminal pH dropped sharply from 6.2 to 5.7 (P<0.05) when dietary concentrate increased from 40% to 60%. A combined metagenome and metatranscriptome sequencing approach identified that this was linked to a sharp decrease in the abundance and expression of genes encoding nicotinamide adenine dinucleotide (NAD)-dependent lactate dehydrogenase (nLDH), catalyzing the enzymatic conversion of pyruvate to lactate (P<0.01), whereas the expression of two genes encoding NAD-independent lactate dehydrogenase (iLDH), catalyzing lactate oxidation to pyruvate, showed no significant concomitant change. Abundance and expression alterations for nLDH- and iLDH-encoding genes were attributable to bacteria from Clostridiales and Bacteroidales, respectively. By analyzing the gene profiles of 9 metagenome bins (MAG) with nLDH-encoding genes and 5 MAG with iLDH-encoding genes, we identified primary and secondary active transporters as being the major types of sugar transporter for lactate-producing bacteria (LPB) and lactate-utilizing bacteria (LUB), respectively. Furthermore, more adenosine triphosphate was required for the phosphorylation of sugars to initiate their catabolic pathways in LPB compared to LUB. Thus, the low dependence of sugar transport systems and catabolic pathways on primary energy sources supports the acid tolerance of LUB from Bacteroidales. It favors ruminal lactate utilization during the adaptation of goats to a high-concentrate diet. This finding has valuable implications for the development of measures to prevent RA.

Abundant resistome determinants in rhizosphere soil of the wild plant Abutilon fruticosum

A metagenomic whole genome shotgun sequencing approach was used for rhizospheric soil micribiome of the wild plant Abutilon fruticosum in order to detect antibiotic resistance genes (ARGs) along with their antibiotic resistance mechanisms and to detect potential risk of these ARGs to human health upon transfer to clinical isolates. The study emphasized the potential risk to human health of such human pathogenic or commensal bacteria, being transferred via food chain or horizontally transferred to human clinical isolates. The top highly abundant rhizospheric soil non-redundant ARGs that are prevalent in bacterial human pathogens or colonizers (commensal) included mtrA, soxR, vanRO, golS, rbpA, kdpE, rpoB2, arr-1, efrA and ileS genes. Human pathogenic/colonizer bacteria existing in this soil rhizosphere included members of genera Mycobacterium, Vibrio, Klebsiella, Stenotrophomonas, Pseudomonas, Nocardia, Salmonella, Escherichia, Citrobacter, Serratia, Shigella, Cronobacter and Bifidobacterium. These bacteria belong to phyla Actinobacteria and Proteobacteria. The most highly abundant resistance mechanisms included antibiotic efflux pump, antibiotic target alteration, antibiotic target protection and antibiotic inactivation. antimicrobial resistance (AMR) families of the resistance mechanism of antibiotic efflux pump included resistance-nodulation-cell division (RND) antibiotic efflux pump (for mtrA, soxR and golS genes), major facilitator superfamily (MFS) antibiotic efflux pump (for soxR gene), the two-component regulatory kdpDE system (for kdpE gene) and ATP-binding cassette (ABC) antibiotic efflux pump (for efrA gene). AMR families of the resistance mechanism of antibiotic target alteration included glycopeptide resistance gene cluster (for vanRO gene), rifamycin-resistant beta-subunit of RNA polymerase (for rpoB2 gene) and antibiotic-resistant isoleucyl-tRNA synthetase (for ileS gene). AMR families of the resistance mechanism of antibiotic target protection included bacterial RNA polymerase-binding protein (for RbpA gene), while those of the resistance mechanism of antibiotic inactivation included rifampin ADP-ribosyltransferase (for arr-1 gene). Better agricultural and food transport practices are required especially for edible plant parts or those used in folkloric medicine.

Analysis of changes in bacterial diversity in healthy and bacterial wilt mulberry samples using metagenomic sequencing and culture-dependent approaches.

Mulberry bacterial wilt is a serious destructive soil-borne disease caused by a complex and diverse group of pathogenic bacteria. Given that the bacterial wilt has been reported to cause a serious damage to the yield and quality of mulberry, therefore, elucidation of its main pathogenic groups is essential in improving our understanding of this disease and for the development of its potential control measures. In this study, combined metagenomic sequencing and culture-dependent approaches were used to investigate the microbiome of healthy and bacterial wilt mulberry samples. The results showed that the healthy samples had higher bacterial diversity compared to the diseased samples. Meanwhile, the proportion of opportunistic pathogenic and drug-resistant bacterial flora represented by Acinetobacter in the diseased samples was increased, while the proportion of beneficial bacterial flora represented by Proteobacteria was decreased. Ralstonia solanacearum species complex (RSSC), Enterobacter cloacae complex (ECC), Klebsiella pneumoniae, K. quasipneumoniae, K. michiganensis, K. oxytoca, and P. ananatis emerged as the main pathogens of the mulberry bacterial wilt. In conclusion, this study provides a valuable reference for further focused research on the bacterial wilt of mulberry and other plants.

Metagenomic and network analyses reveal key players in nitrification in upland agricultural soils.

Nitrification, a key step in soil nitrogen cycling, is a biologically mediated process crucial to the ecological environment. However, how nitrifiers drive nitrification under different soil properties and climatic factors at large spatial scales is poorly understood. Here, using metagenomic sequencing and network-based approaches, we identified key nitrifying species of upland agricultural soils in northern China, which spans a wide range of climates and geographic distances. We found that potential nitrification rates (PNRs) varied in different soils and were positively correlated with soil pH (5.42-8.46) and mean annual temperature (MAT) and negatively correlated with the C/N ratio. Network analysis revealed that one module (module 3) was significantly correlated with PNR. In this module, 16 dominant nodes were associated with AOB Nitrosomonas and most nodes were significantly correlated with environmental factors, suggesting that abiotic conditions are important for determining the assembly of these key nitrifiers. Our study advanced the understanding of the key nitrifying populations and their environmental drivers in upland agricultural soil across different soil and climate types.