Integrated genomic and functional analyses of human skin-associated Staphylococcus reveal extensive inter- and intra-species diversity.

Human skin is stably colonized by a distinct microbiota that functions together with epidermal cells to maintain a protective physical barrier. Staphylococcus, a prominent genus of the skin microbiota, participates in colonization resistance, tissue repair, and host immune regulation in strain-specific manners. To unlock the potential of engineering skin microbial communities, we aim to characterize the diversity of this genus within the context of the skin environment. We reanalyzed an extant 16S rRNA amplicon dataset obtained from distinct body sites of healthy volunteers, providing a detailed biogeographic depiction of staphylococcal species that colonize our skin. S. epidermidis, S. capitis, and S. hominis were the most abundant staphylococcal species present in all volunteers and were detected at all body sites. Pan-genome analysis of isolates from these three species revealed that the genus-core was dominated by central metabolism genes. Species-restricted-core genes encoded known host colonization functions. The majority (~68%) of genes were detected only in a fraction of isolate genomes, underscoring the immense strain-specific gene diversity. Conspecific genomes grouped into phylogenetic clades, exhibiting body site preference. Each clade was enriched for distinct gene sets that are potentially involved in site tropism. Finally, we conducted gene expression studies of select isolates showing variable growth phenotypes in skin-like medium. In vitro expression revealed extensive intra- and inter-species gene expression variation, substantially expanding the functional diversification within each species. Our study provides an important resource for future ecological and translational studies to examine the role of shared and strain-specific staphylococcal genes within the skin environment.

Amplidiff: an optimized amplicon sequencing approach to estimating lineage abundances in viral metagenomes.

BACKGROUND: Metagenomic profiling algorithms commonly rely on genomic differences between lineages, strains, or species to infer the relative abundances of sequences present in a sample. This observation plays an important role in the analysis of diverse microbial communities, where targeted sequencing of 16S and 18S rRNA, both well-known hypervariable genomic regions, have led to insights into microbial diversity and the discovery of novel organisms. However, the variable nature of discriminatory regions can also act as a double-edged sword, as the sought-after variability can make it difficult to design primers for their amplification through PCR. Moreover, the most variable regions are not necessarily the most informative regions for the purpose of differentiation; one should focus on regions that maximize the number of lineages that can be distinguished. RESULTS: Here we present AmpliDiff, a computational tool that simultaneously finds highly discriminatory genomic regions in viral genomes of a single species, as well as primers allowing for the amplification of these regions. We show that regions and primers found by AmpliDiff can be used to accurately estimate relative abundances of SARS-CoV-2 lineages, for example in wastewater sequencing data. We obtain errors that are comparable with using whole genome information to estimate relative abundances. Furthermore, our results show that AmpliDiff is robust against incomplete input data and that primers designed by AmpliDiff also bind to genomes sampled months after the primers were selected. CONCLUSIONS: With AmpliDiff we provide an effective, cost-efficient alternative to whole genome sequencing for estimating lineage abundances in viral metagenomes.

SpeciateIT and vSpeciateDB: novel, fast, and accurate per sequence 16S rRNA gene taxonomic classification of vaginal microbiota.

BACKGROUND: Clustering of sequences into operational taxonomic units (OTUs) and denoising methods are a mainstream stopgap to taxonomically classifying large numbers of 16S rRNA gene sequences. Environment-specific reference databases generally yield optimal taxonomic assignment. RESULTS: We developed SpeciateIT, a novel taxonomic classification tool which rapidly and accurately classifies individual amplicon sequences ( https://github.com/Ravel-Laboratory/speciateIT ). We also present vSpeciateDB, a custom reference database for the taxonomic classification of 16S rRNA gene amplicon sequences from vaginal microbiota. We show that SpeciateIT requires minimal computational resources relative to other algorithms and, when combined with vSpeciateDB, affords accurate species level classification in an environment-specific manner. CONCLUSIONS: Herein, two resources with new and practical importance are described. The novel classification algorithm, SpeciateIT, is based on 7th order Markov chain models and allows for fast and accurate per-sequence taxonomic assignments (as little as 10 min for 107 sequences). vSpeciateDB, a meticulously tailored reference database, stands as a vital and pragmatic contribution. Its significance lies in the superiority of this environment-specific database to provide more species-resolution over its universal counterparts.

DengueSeq: a pan-serotype whole genome amplicon sequencing protocol for dengue virus.

BACKGROUND: The increasing burden of dengue virus on public health due to more explosive and frequent outbreaks highlights the need for improved surveillance and control. Genomic surveillance of dengue virus not only provides important insights into the emergence and spread of genetically diverse serotypes and genotypes, but it is also critical to monitor the effectiveness of newly implemented control strategies. Here, we present DengueSeq, an amplicon sequencing protocol, which enables whole-genome sequencing of all four dengue virus serotypes. RESULTS: We developed primer schemes for the four dengue virus serotypes, which can be combined into a pan-serotype approach. We validated both approaches using genetically diverse virus stocks and clinical specimens that contained a range of virus copies. High genome coverage (>95%) was achieved for all genotypes, except DENV2 (genotype VI) and DENV 4 (genotype IV) sylvatics, with similar performance of the serotype-specific and pan-serotype approaches. The limit of detection to reach 70% coverage was 10-100 RNA copies/µL for all four serotypes, which is similar to other commonly used primer schemes. DengueSeq facilitates the sequencing of samples without known serotypes, allows the detection of multiple serotypes in the same sample, and can be used with a variety of library prep kits and sequencing instruments. CONCLUSIONS: DengueSeq was systematically evaluated with virus stocks and clinical specimens spanning the genetic diversity within each of the four dengue virus serotypes. The primer schemes can be plugged into existing amplicon sequencing workflows to facilitate the global need for expanded dengue virus genomic surveillance.

A retrospective analysis of P. falciparum drug resistance markers detects an early (2016/17) high prevalence of the k13 C469Y mutation in asymptomatic infections in Northern Uganda.

The emergence of drug-resistant Plasmodium falciparum parasites in sub-Saharan Africa will substantially challenge malaria control. Here, we evaluated the frequency of common drug resistance markers among adolescents from Northern Uganda with asymptomatic infections. We used an established amplicon deep sequencing strategy to screen dried blood spot samples collected from 2016 to 2017 during a reported malaria epidemic within the districts of Kitgum and Pader in Northern Uganda. We screened single-nucleotide polymorphisms within: kelch13 (Pfk13), dihydropteroate synthase (Pfdhps), multidrug resistance-1 (Pfmdr1), dihydrofolate reductase (Pfdhfr), and apical membrane antigen (Pfama1) genes. Within the study population, the median age was 15 years (14.3-15.0, 95% CI), and 54.9% (78/142) were Plasmodium positive by 18S rRNA qPCR, which were subsequently targeted for sequencing analysis. We observed a high frequency of resistance markers particularly for sulfadoxine-pyrimethamine (SP), with no wild-type-only parasites observed for Pfdhfr (N51I, C59R, and S108N) and Pfdhps (A437G and K540E) mutations. Within Pfmdr1, mixed infections were common for NF/NY (98.5%). While for artemisinin resistance, in kelch13, there was a high frequency of C469Y (34%). Using the pattern for Pfama1, we found a high level of polygenomic infections with all individuals presenting with complexity of infection greater than 2 with a median of 6.9. The high frequency of the quintuple SP drug-resistant parasites and the C469Y artemisinin resistance-associated mutation in asymptomatic individuals suggests an earlier high prevalence than previously reported from symptomatic malaria surveillance studies (in 2016/2017). Our data demonstrate the urgency for routine genomic surveillance programs throughout Africa and the value of deep sequencing.

Diversity of the Rysto gene conferring resistance to potato virus Y in wild relatives of potato.

BACKGROUND: Potato virus Y (PVY) is among the economically most damaging viral pathogen in production of potato (Solanum tuberosum) worldwide. The gene Rysto derived from the wild potato relative Solanum stoloniferum confers extreme resistance to PVY. RESULTS: The presence and diversity of Rysto were investigated in wild relatives of potato (298 genotypes representing 29 accessions of 26 tuber-bearing Solanum species) using PacBio amplicon sequencing. A total of 55 unique Rysto-like sequences were identified in 72 genotypes representing 12 accessions of 10 Solanum species and six resistant controls (potato cultivars Alicja, Bzura, Hinga, Nimfy, White Lady and breeding line PW363). The 55 Rysto-like sequences showed 89.87 to 99.98% nucleotide identity to the Rysto reference gene, and these encoded in total 45 unique protein sequences. While Rysto-like26 identified in Alicja, Bzura, White Lady and Rysto-like16 in PW363 encode a protein identical to the Rysto reference, the remaining 44 predicted Rysto-like proteins were 65.93 to 99.92% identical to the reference. Higher levels of diversity of the Rysto-like sequences were found in the wild relatives of potato than in the resistant control cultivars. The TIR and NB-ARC domains were the most conserved within the Rysto-like proteins, while the LRR and C-JID domains were more variable. Several Solanum species, including S. antipoviczii and S. hougasii, showed resistance to PVY. This study demonstrated Hyoscyamus niger, a Solanaceae species distantly related to Solanum, as a host of PVY. CONCLUSIONS: The new Rysto-like variants and the identified PVY resistant potato genotypes are potential resistance sources against PVY in potato breeding. Identification of H. niger as a host for PVY is important for cultivation of this plant, studies on the PVY management, its ecology, and migrations. The amplicon sequencing based on PacBio SMRT and the following data analysis pipeline described in our work may be applied to obtain the nucleotide sequences and analyze any full-length genes from any, even polyploid, organisms.

Development of an automated amplicon-based next-generation sequencing pipeline for rapid detection of bacteria and fungi directly from clinical specimens.

The timely identification of microbial pathogens is essential to guide targeted antimicrobial therapy and ultimately, successful treatment of an infection. However, the yield of standard microbiology testing (SMT) is directly related to the duration of antecedent antimicrobial therapy as SMT culture methods are dependent on the recovery of viable organisms, the fastidious nature of certain pathogens, and other pre-analytic factors. In the last decade, metagenomic next-generation sequencing (mNGS) has been successfully utilized as a diagnostic tool for various applications within the clinical laboratory. However, mNGS is resource, time, and labor-intensive-requiring extensive laborious preliminary benchwork, followed by complex bioinformatic analysis. We aimed to address these shortcomings by developing a largely Automated targeted Metagenomic next-generation sequencing (tmNGS) PipeLine for rapId inFectIous disEase Diagnosis (AMPLIFIED) to detect bacteria and fungi directly from clinical specimens. Therefore, AMPLIFIED may serve as an adjunctive approach to complement SMT. This tmNGS pipeline requires less than 1 hour of hands-on time before sequencing and less than 2 hours of total processing time, including bioinformatic analysis. We performed tmNGS on 50 clinical specimens with concomitant cultures to assess feasibility and performance in the hospital laboratory. Of the 50 specimens, 34 (68%) were from true clinical infections. Specimens from cases of true infection were more often tmNGS positive compared to those from the non-infected group (82.4% vs 43.8%, respectively, P = 0.0087). Overall, the clinical sensitivity of AMPLIFIED was 54.6% with 85.7% specificity, equating to 70.6% and 75% negative and positive predictive values, respectively. AMPLIFIED represents a rapid supplementary approach to SMT; the typical time from specimen receipt to identification of potential pathogens by AMPLIFIED is roughly 24 hours which is markedly faster than the days, weeks, and months required to recover bacterial, fungal, and mycobacterial pathogens by culture, respectively. IMPORTANCE: To our knowledge, this represents the first application of an automated sequencing and bioinformatics pipeline in an exclusively pediatric population. Next-generation sequencing is time-consuming, labor-intensive, and requires experienced personnel; perhaps contributing to hesitancy among clinical laboratories to adopt such a test. Here, we report a strong case for use by removing these barriers through near-total automation of our sequencing pipeline.

Pathogen-microbiome interactions and the virulence of an entomopathogenic fungus.

Bacteria shape interactions between hosts and fungal pathogens. In some cases, bacteria associated with fungi are essential for pathogen virulence. In other systems, host-associated microbiomes confer resistance against fungal pathogens. We studied an aphid-specific entomopathogenic fungus called Pandora neoaphidis in the context of both host and pathogen microbiomes. Aphids host several species of heritable bacteria, some of which confer resistance against Pandora. We first found that spores that emerged from aphids that harbored protective bacteria were less virulent against subsequent hosts and did not grow on plate media. We then used 16S amplicon sequencing to study the bacterial microbiome of fungal mycelia and spores during plate culturing and host infection. We found that the bacterial community is remarkably stable in culture despite dramatic changes in pathogen virulence. Last, we used an experimentally transformed symbiont of aphids to show that Pandora can acquire host-associated bacteria during infection. Our results uncover new roles for bacteria in the dynamics of aphid-pathogen interactions and illustrate the importance of the broader microbiological context in studies of fungal pathogenesis. IMPORTANCE: Entomopathogenic fungi play important roles in the population dynamics of many insect species. Understanding the factors shaping entomopathogen virulence is critical for agricultural management and for the use of fungi in pest biocontrol. We show that heritable bacteria in aphids, which confer protection to their hosts against fungal entomopathogens, influence virulence against subsequent hosts. Aphids reproduce asexually and are typically surrounded by genetically identical offspring, and thus these effects likely shape the dynamics of fungal disease in aphid populations. Furthermore, fungal entomopathogens are known to rapidly lose virulence in lab culture, complicating their laboratory use. We show that this phenomenon is not driven by changes in the associated bacterial microbiome. These results contribute to our broader understanding of the aphid model system and shed light on the biology of the Entomophthorales-an important but understudied group of fungi.

Microbiome analysis of the restricted bacteria in radioactive element-containing water at the Fukushima Daiichi Nuclear Power Station.

A major incident occurred at the Fukushima Daiichi Nuclear Power Station following the tsunami triggered by the Tohoku-Pacific Ocean Earthquake in March 2011, whereby seawater entered the torus room in the basement of the reactor building. Here, we identify and analyze the bacterial communities in the torus room water and several environmental samples. Samples of the torus room water (1 × 109 Bq137Cs/L) were collected by the Tokyo Electric Power Company Holdings from two sampling points between 30 cm and 1 m from the bottom of the room (TW1) and the bottom layer (TW2). A structural analysis of the bacterial communities based on 16S rRNA amplicon sequencing revealed that the predominant bacterial genera in TW1 and TW2 were similar. TW1 primarily contained the genus Limnobacter, a thiosulfate-oxidizing bacterium. γ-Irradiation tests on Limnobacter thiooxidans, the most closely related phylogenetically found in TW1, indicated that its radiation resistance was similar to ordinary bacteria. TW2 predominantly contained the genus Brevirhabdus, a manganese-oxidizing bacterium. Although bacterial diversity in the torus room water was lower than seawater near Fukushima, ~70% of identified genera were associated with metal corrosion. Latent environment allocation-an analytical technique that estimates habitat distributions and co-detection analyses-revealed that the microbial communities in the torus room water originated from a distinct blend of natural marine microbial and artificial bacterial communities typical of biofilms, sludge, and wastewater. Understanding the specific bacteria linked to metal corrosion in damaged plants is important for advancing decommissioning efforts. IMPORTANCE: In the context of nuclear power station decommissioning, the proliferation of microorganisms within the reactor and piping systems constitutes a formidable challenge. Therefore, the identification of microbial communities in such environments is of paramount importance. In the aftermath of the Fukushima Daiichi Nuclear Power Station accident, microbial community analysis was conducted on environmental samples collected mainly outside the site. However, analyses using samples from on-site areas, including adjacent soil and seawater, were not performed. This study represents the first comprehensive analysis of microbial communities, utilizing meta 16S amplicon sequencing, with a focus on environmental samples collected from the radioactive element-containing water in the torus room, including the surrounding environments. Some of the identified microbial genera are shared with those previously identified in spent nuclear fuel pools in countries such as France and Brazil. Moreover, our discussion in this paper elucidates the correlation of many of these bacteria with metal corrosion.

Unraveling the distribution pattern and driving forces of soil microorganisms under geographic barriers.

The Altai Mountains (ALE) and the Greater Khingan Mountains (GKM) in northern China are forest regions dominated by coniferous trees. These geographically isolated regions provide an ideal setting for studying microbial biogeographic patterns. In this study, we employed high-throughput techniques to obtain DNA sequences of soil myxomycetes, bacteria, and fungi and explored the mechanisms underlying the assembly of both local and cross-regional microbial communities in relation to environmental factors. Our investigation revealed that the environmental heterogeneity in ALE and GKM significantly affected the succession and assembly of soil bacterial communities at cross-regional scales. Specifically, the optimal environmental factors affecting bacterial Bray-Curtis similarity were elevation and temperature seasonality. The spatial factors and climate change impact on bacterial communities under the geographical barriers surpassed that of local soil microenvironments. The assembly pattern of bacterial communities transitions from local drift to cross-regional heterogeneous selection. Environmental factors had a relatively weak influence on myxomycetes and fungi. Both soil myxomycetes and fungi faced considerable dispersal limitation at local and cross-regional scales, ultimately leading to weak geographical distribution patterns.IMPORTANCEThe impact of environmental selection and dispersal on the soil microbial spatial distribution is a key concern in microbial biogeography, particularly in large-scale geographical patterns. However, our current understanding remains limited. Our study found that soil bacteria displayed a distinct cross-regional geographical distribution pattern, primarily influenced by environmental selection. Conversely, the cross-regional geographical distribution patterns of soil myxomycetes and fungi were relatively weak. Their composition exhibited a weak association with the environment at local and cross-regional scales, with assembly primarily driven by dispersal limitation.

Highly sensitive wastewater surveillance of SARS-CoV-2 variants by targeted next-generation amplicon sequencing provides early warning of incursion in Victoria, Australia.

The future of the COVID pandemic and its public health and societal impact will be determined by the profile and spread of emerging variants and the timely identification and response to them. Wastewater surveillance of SARS-CoV-2 has been widely adopted in many countries across the globe and has played an important role in tracking infection levels and providing useful epidemiological information that cannot be adequately captured by clinical testing alone. However, novel variants can emerge rapidly, spread globally, and markedly alter the trajectory of the pandemic, as exemplified by the Delta and Omicron variants. Most mutations linked to the emergence of new SARS-CoV-2 variants are found within variable regions of the SARS-CoV-2 Spike protein. We have developed a duplex hemi-nested PCR method that, coupled with short amplicon sequencing, allows simultaneous typing of two of the most highly variable and informative regions of the Spike gene: the N-terminal domain and the receptor binding motif. Using this method in an operationalized public health program, we identified the first known incursion of Omicron BA.1 into Victoria, Australia and demonstrated how sensitive amplicon sequencing methods can be combined with wastewater surveillance as a relatively low-cost solution for early warning of variant incursion and spread.IMPORTANCEThis study offers a rapid, cost-effective, and sensitive approach for monitoring SARS-CoV-2 variants in wastewater. The method's flexibility permits timely modifications, enabling the integration of emerging variants and adaptations to evolving SARS-CoV-2 genetics. Of particular significance for low- and middle-income regions with limited surveillance capabilities, this technique can potentially be utilized to study a range of pathogens or viruses that possess diverse genetic sequences, similar to influenza.

Development of a novel mycobiome diagnostic for fungal infection.

BACKGROUND: Amplicon-based mycobiome analysis has the potential to identify all fungal species within a sample and hence could provide a valuable diagnostic assay for use in clinical mycology settings. In the last decade, the mycobiome has been increasingly characterised by targeting the internal transcribed spacer (ITS) regions. Although ITS targets give broad coverage and high sensitivity, they fail to provide accurate quantitation as the copy number of ITS regions in fungal genomes is highly variable even within species. To address these issues, this study aimed to develop a novel NGS fungal diagnostic assay using an alternative amplicon target. METHODS: Novel universal primers were designed to amplify a highly diverse single copy and uniformly sized DNA target (Tef1) to enable mycobiome analysis on the Illumina iSeq100 which is a low cost, small footprint and simple to use next-generation sequencing platform. To enable automated analysis and rapid results, a streamlined bioinformatics workflow and sequence database were also developed. Sequencing of mock fungal communities was performed to compare the Tef1 assay and established ITS1-based method. The assay was further evaluated using clinical respiratory samples and the feasibility of using internal spike-in quantitative controls was assessed. RESULTS: The Tef1 assay successfully identified and quantified Aspergillus, Penicillium, Candida, Cryptococcus, Rhizopus, Fusarium and Lomentospora species from mock communities. The Tef1 assay was also capable of differentiating closely related species such as A. fumigatus and A. fischeri. In addition, it outperformed ITS1 at identifying A. fumigatus and other filamentous pathogens in mixed fungal communities (in the presence or absence of background human DNA). The assay could detect as few as 2 haploid genome equivalents of A. fumigatus from clinical respiratory samples. Lastly, spike-in controls were demonstrated to enable semi-quantitation of A. fumigatus load in clinical respiratory samples using sequencing data. CONCLUSIONS: This study has developed and tested a novel metabarcoding target and found the assay outperforms ITS1 at identifying clinically relevant filamentous fungi. The assay is a promising diagnostic candidate that could provide affordable NGS analysis to clinical mycology laboratories.

Rhizosphere microbial community construction during the latitudinal spread of the invader Chromolaena odorata.

The colonization of alien plants in new habitats is typically facilitated by microorganisms present in the soil environment. However, the diversity and structure of the archaeal, bacterial, and fungal communities in the latitudinal spread of alien plants remain unclear. In this study, the rhizosphere and bulk soil of Chromolaena odorata were collected from five latitudes in Pu' er city, Yunnan Province, followed by amplicon sequencing of the soil archaeal, bacterial, and fungal communities. Alpha and beta diversity results revealed that the richness indices and the structures of the archaeal, bacterial, and fungal communities significantly differed along the latitudinal gradient. Additionally, significant differences were observed in the bacterial Shannon index, as well as in the structures of the bacterial and fungal communities between the rhizosphere and bulk soils. Due to the small spatial scale, trends of latitudinal variation in the archaeal, bacterial, and fungal communities were not pronounced. Total potassium, total phosphorus, available nitrogen, available potassium and total nitrogen were the important driving factors affecting the soil microbial community structure. Compared with those in bulk soil, co-occurrence networks in rhizosphere microbial networks presented lower complexity but greater modularity and positive connections. Among the main functional fungi, arbuscular mycorrhizae and soil saprotrophs were more abundant in the bulk soil. The significant differences in the soil microbes between rhizosphere and bulk soils further underscore the impact of C. odorata invasion on soil environments. The significant differences in the soil microbiota along latitudinal gradients, along with specific driving factors, demonstrate distinct nutrient preferences among archaea, bacteria, and fungi and indicate complex microbial responses to soil nutrient elements following the invasion of C. odorata.

Characteristics of the oral and gastric microbiome in patients with early-stage intramucosal esophageal squamous cell carcinoma.

BACKGROUND: Oral microbiome dysbacteriosis has been reported to be associated with the pathogenesis of advanced esophageal cancer. However, few studies investigated the potential role of oral and gastric microbiota in early-stage intramucosal esophageal squamous carcinoma (EIESC). METHOD: A total of 104 samples were collected from 31 patients with EIESC and 21 healthy controls. The compositions of oral and gastric microbiota were analyzed using 16 S rRNA V3-V4 amplicon sequencing. Linear discriminant analysis effect size (LEfSe) analysis was performed to assess taxonomic differences between groups. The correlation between oral microbiota and clinicopathological factors was evaluated using Spearman correlation analysis. Additionally, co-occurrence networks were established and random forest models were utilized to identify significant microbial biomarkers for distinguishing between the EIESC and control groups. RESULTS: A total of 292 oral genera and 223 species were identified in both EIESC and healthy controls. Six oral genera were remarkably enriched in EIESC groups, including the genera Porphyromonas, Shigella, Subdoligranulum, Leptotrichia, Paludibacter, and Odoribacter. LEfSe analysis identified genera Porphyromonas and Leptotrichia with LDA scores > 3. In the random forest model, Porphyromonas endodontalis ranked the top microbial biomarker to differentiate EIESC from controls. The elimination rate of Porphyromonas endodontalis from the oral cavity to the stomach was also dramatically decreased in the EIESC group than controls. In the microbial co-occurrence network, Porphyromonas endodontalis was positively correlated with Prevotella tannerae and Prevotella intermedia and was negatively correlated with Veillonella dispar. CONCLUSION: Our study potentially indicates that the dysbacteriosis of both the oral and gastric microbiome was associated with EIESC. Larger scale studies and experimental animal models are urgently needed to confirm the possible role of microbial dysbacteriosis in the pathogenesis of EIESC. (Chinese Clinical Trial Registry Center, ChiCTR2200063464, Registered 07 September 2022, https://www.chictr.org.cn/showproj.html?proj=178563).

A culture-independent approach, supervised machine learning, and the characterization of the microbial community composition of coastal areas across the Bay of Bengal and the Arabian Sea.

BACKGROUND: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic activities, and recreational impacts. We explored three main factors influencing the differences between these coastlines: The Bay of Bengal's shallower depth and lower salinity; upwelling phenomena due to the thermocline in the Arabian Sea; and high tides that can cause strong currents that transport pollutants and debris. RESULTS: The microbial diversity in GA was significantly higher than that in AP, which might be attributed to differences in temperature, soil type, and vegetation cover. 16S rRNA amplicon sequencing and bioinformatics analysis indicated the presence of diverse microbial phyla, including candidate phyla radiation (CPR). Statistical analysis, random forest regression, and supervised machine learning models classification confirm the diversity of the microbiome accurately. Furthermore, we have identified 450 cultures of heterotrophic, biotechnologically important bacteria. Some strains were identified as novel taxa based on 16S rRNA gene sequencing, showing promising potential for further study. CONCLUSION: Thus, our study provides valuable insights into the microbial diversity and pollution levels of coastal areas in AP and GA. These findings contribute to a better understanding of the impact of anthropogenic activities and climate variations on biology of coastal ecosystems and biodiversity.

Long-term push-pull cropping system shifts soil and maize-root microbiome diversity paving way to resilient farming system.

BACKGROUND: The soil biota consists of a complex assembly of microbial communities and other organisms that vary significantly across farming systems, impacting soil health and plant productivity. Despite its importance, there has been limited exploration of how different cropping systems influence soil and plant root microbiomes. In this study, we investigated soil physicochemical properties, along with soil and maize-root microbiomes, in an agroecological cereal-legume companion cropping system known as push-pull technology (PPT). This system has been used in agriculture for over two decades for insect-pest management, soil health improvement, and weed control in sub-Saharan Africa. We compared the results with those obtained from maize-monoculture (Mono) cropping system. RESULTS: The PPT cropping system changed the composition and diversity of soil and maize-root microbial communities, and led to notable improvements in soil physicochemical characteristics compared to that of the Mono cropping system. Distinct bacterial and fungal genera played a crucial role in influencing the variation in microbial diversity within these cropping systems. The relative abundance of fungal genera Trichoderma, Mortierella, and Bionectria and bacterial genera Streptomyces, RB41, and Nitrospira were more enriched in PPT. These microbial communities are associated with essential ecosystem services such as plant protection, decomposition, carbon utilization, bioinsecticides production, nitrogen fixation, nematode suppression, phytohormone production, and bioremediation. Conversely, pathogenic associated bacterial genus including Bryobacter were more enriched in Mono-root. Additionally, the Mono system exhibited a high relative abundance of fungal genera such as Gibberella, Neocosmospora, and Aspergillus, which are linked to plant diseases and food contamination. Significant differences were observed in the relative abundance of the inferred metabiome functional protein pathways including syringate degradation, L-methionine biosynthesis I, and inosine 5'-phosphate degradation. CONCLUSION: Push-pull cropping system positively influences soil and maize-root microbiomes and enhances soil physicochemical properties. This highlights its potential for agricultural and environmental sustainability. These findings contribute to our understanding of the diverse ecosystem services offered by this cropping system where it is practiced regarding the system's resilience and functional redundancy. Future research should focus on whether PPT affects the soil and maize-root microbial communities through the release of plant metabolites from the intercrop root exudates or through the alteration of the soil's nutritional status, which affects microbial enzymatic activities.

The resurgence of influenza A/H3N2 virus in Australia after the relaxation of COVID-19 restrictions during the 2022 season.

This study retrospectively analyzed the genetic characteristics of influenza A H3N2 (A/H3N2) viruses circulating in New South Wales (NSW), the Australian state with the highest number of influenza cases in 2022, and explored the phylodynamics of A/H3N2 transmission within Australia during this period. Sequencing was performed on 217 archived specimens, and A/H3N2 evolution and spread within Australia were analyzed using phylogenetic and phylodynamic methods. Hemagglutinin genes of all analyzed NSW viruses belonged to subclade 3C.2a1b.2a.2 and clustered together with the 2022 vaccine strain. Complete genome analysis of NSW viruses revealed highly frequent interclade reassortments between subclades 3C.2a1b.2a.2 and 3C.2a1b.1a. The estimated earliest introduction time of the dominant subgroup 3C.2a1b.2a.2a.1 in Australia was February 22, 2022 (95% highest posterior density: December 19, 2021-March 13, 2022), following the easing of Australian travel restrictions, suggesting a possible international source. Phylogeographic analysis revealed that Victoria drove the transmission of A/H3N2 viruses across the country during this season, while NSW did not have a dominant role in viral dissemination to other regions. This study highlights the importance of continuous surveillance and genomic characterization of influenza viruses in the postpandemic era, which can inform public health decision-making and enable early detection of novel strains with pandemic potential.

Environmental heterogeneity structures root-associated fungal communities in Daphne arbuscula (Thymelaeaceae), a shrub adapted to extreme rocky habitats.

Rocky habitats, globally distributed ecosystems, harbour diverse biota, including numerous endemic and endangered species. Vascular plants thriving in these environments face challenging abiotic conditions, requiring diverse morphological and physiological adaptations. Their engagement with the surrounding microbiomes is, however, equally vital for their adaptation, fitness, and long-term survival. Nevertheless, there remains a lack of understanding surrounding this complex interplay within this fascinating biotic ecosystem. Using microscopic observations and metabarcoding analyses, we examined the fungal abundance and diversity in the root system of the rock-dwelling West Carpathian endemic shrub, Daphne arbuscula (Thymelaeaceae). We explored the diversification of root-associated fungal communities in relation to microclimatic variations across the studied sites. We revealed extensive colonization of the Daphne roots by diverse taxonomic fungal groups attributed to different ecological guilds, predominantly plant pathogens, dark septate endophytes (DSE), and arbuscular mycorrhizal fungi (AMF). Notably, differences in taxonomic composition and ecological guilds emerged between colder and warmer microenvironments. Apart from omnipresent AMF, warmer sites exhibited a prevalence of plant pathogens, while colder sites were characterized by a dominance of DSE. This mycobiome diversification, most likely triggered by the environment, suggests that D. arbuscula populations in warmer areas may be more vulnerable to fungal diseases, particularly in the context of global climate change.

Microbiome diversity and zoonotic bacterial pathogen prevalence in Peromyscus mice from agricultural landscapes and synanthropic habitat.

Rodents are key reservoirs of zoonotic pathogens and play an important role in disease transmission to humans. Importantly, anthropogenic land-use change has been found to increase the abundance of rodents that thrive in human-built environments (synanthropic rodents), particularly rodent reservoirs of zoonotic disease. Anthropogenic environments also affect the microbiome of synanthropic wildlife, influencing wildlife health and potentially introducing novel pathogens. Our objective was to examine the effect of agricultural development and synanthropic habitat on microbiome diversity and the prevalence of zoonotic bacterial pathogens in wild Peromyscus mice to better understand the role of these rodents in pathogen maintenance and transmission. We conducted 16S amplicon sequencing on faecal samples using long-read nanopore sequencing technology to characterize the rodent microbiome. We compared microbiome diversity and composition between forest and synanthropic habitats in agricultural and undeveloped landscapes and screened for putative pathogenic bacteria. Microbiome richness, diversity, and evenness were higher in the agricultural landscape and synanthropic habitat compared to undeveloped-forest habitat. Microbiome composition also differed significantly between agricultural and undeveloped landscapes and forest and synanthropic habitats. We detected overall low diversity and abundance of putative pathogenic bacteria, though putative pathogens were more likely to be found in mice from the agricultural landscape. Our findings show that landscape- and habitat-level anthropogenic factors affect Peromyscus microbiomes and suggest that landscape-level agricultural development may be important to predict zoonotic pathogen prevalence. Ultimately, understanding how anthropogenic land-use change and synanthropy affect rodent microbiomes and pathogen prevalence is important to managing transmission of rodent-borne zoonotic diseases to humans.

Plasmodium falciparum transmission in the highlands of Ethiopia is driven by closely related and clonal parasites.

Malaria cases are frequently recorded in the Ethiopian highlands even at altitudes above 2000 m. The epidemiology of malaria in the Ethiopian highlands, and, in particular, the role of importation by human migration from the highly endemic lowlands is not well understood. We sequenced 187 Plasmodium falciparum samples from two sites in the Ethiopian highlands, Gondar (n = 159) and Ziway (n = 28), using a multiplexed droplet digital PCR (ddPCR)-based amplicon sequencing method targeting 35 microhaplotypes and drug resistance loci. Here, we characterize the parasite population structure and genetic relatedness. We identify moderate parasite diversity (mean HE : 0.54) and low infection complexity (74.9% monoclonal). A significant percentage of infections share microhaplotypes, even across transmission seasons and sites, indicating persistent local transmission. We identify multiple clusters of clonal or near-clonal infections, highlighting high genetic relatedness. Only 6.3% of individuals diagnosed with P. falciparum reported recent travel. Yet, in clonal or near-clonal clusters, infections of travellers were frequently observed first in time, suggesting that parasites may have been imported and then transmitted locally. 31.1% of infections are pfhrp2-deleted and 84.4% pfhrp3-deleted, and 28.7% have pfhrp2/3 double deletions. Parasites with pfhrp2/3 deletions and wild-type parasites are genetically distinct. Mutations associated with resistance to sulphadoxine-pyrimethamine or suggested to reduce sensitivity to lumefantrine are observed at near-fixation. In conclusion, genomic data corroborate local transmission and the importance of intensified control in the Ethiopian highlands.