RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency

Exploring the potential of dental calculus to shed light on past human migrations in Oceania

The Pacific islands and Island Southeast Asia have experienced multiple waves of human migrations, providing a case study for exploring the potential of ancient microbiomes to study human migration. We perform a metagenomic study of archaeological dental calculus from 102 individuals, originating from 10 Pacific islands and 1 island in Island Southeast Asia spanning ~3000 years. Oral microbiome DNA preservation in calculus is far higher than that of human DNA in archaeological bone, and comparable to that of calculus from temperate regions. Oral microbial community composition is minimally driven by time period and geography in Pacific and Island Southeast Asia calculus, but is found to be distinctive compared to calculus from Europe, Africa, and Asia. Phylogenies of individual bacterial species in Pacific and Island Southeast Asia calculus reflect geography. Archaeological dental calculus shows good preservation in tropical regions and the potential to yield information about past human migrations, complementing studies of the human genome.

Interrelation of the spatial and genetic structure of tick-borne encephalitis virus, its reservoir host (Myodes glareolus), and its vector (Ixodes ricinus) in a natural focus area

Tick-borne encephalitis (TBE) virus is considered the medically most important arthropod-borne virus in Europe. Although TBE is endemic throughout central Europe, ticks and rodents determine its maintenance in small, difficult-to-assess, natural foci. We investigated the interrelation between the population genetics of the main TBE virus (TBEV) vector tick (Ixodes ricinus), the most important reservoir host (Myodes glareolus, syn. Clethrionomys glareolus), and TBEV. Rodents and ticks were sampled on 15 sites within an exploratory study area, which has been screened regularly for TBEV occurrence in ticks for more than 10 years. On all 15 sites, ticks and bank voles were sampled, screened for TBEV presence via serology and RT-PCR, and genetically examined. Moreover, TBEV isolates derived from these analyses were sequenced. In long-term TBEV foci bank vole populations show extraordinary genetic constitutions, leading to a particular population structure, whereas ticks revealed a panmictic genetic structure overall sampling sites. Landscape genetics and habitat connectivity modeling (analysis of isolation by resistance) showed no landscape-related barriers explaining the genetic structure of the bank vole populations. The results suggest that bank voles do not simply serve as TBEV reservoirs, but their genetic composition appears to have a significant influence on establishing and maintaining long-term natural TBEV foci, whereas the genetic structure of TBEV's main vector I. ricinus does not play an important role in the sustainability of long-term TBEV foci. A thorough investigation of how and to which extent TBEV and M. glareolus genetics are associated is needed to further unravel the underlying mechanisms.

Widespread exposure to SARS-CoV-2 in wildlife communities

Pervasive SARS-CoV-2 infections in humans have led to multiple transmission events to animals. While SARS-CoV-2 has a potential broad wildlife host range, most documented infections have been in captive animals and a single wildlife species, the white-tailed deer. The full extent of SARS-CoV-2 exposure among wildlife communities and the factors that influence wildlife transmission risk remain unknown. We sampled 23 species of wildlife for SARS-CoV-2 and examined the effects of urbanization and human use on seropositivity. Here, we document positive detections of SARS-CoV-2 RNA in six species, including the deer mouse, Virginia opossum, raccoon, groundhog, Eastern cottontail, and Eastern red bat between May 2022-September 2023 across Virginia and Washington, D.C., USA. In addition, we found that sites with high human activity had three times higher seroprevalence than low human-use areas. We obtained SARS-CoV-2 genomic sequences from nine individuals of six species which were assigned to seven Pango lineages of the Omicron variant. The close match to variants circulating in humans at the time suggests at least seven recent human-to-animal transmission events. Our data support that exposure to SARS-CoV-2 has been widespread in wildlife communities and suggests that areas with high human activity may serve as points of contact for cross-species transmission.

Metatranscriptomic Analysis Reveals Synergistic Activities of Comammox and Anammox Bacteria in Full-Scale Attached Growth Nitrogen Removal System

Leveraging comammox Nitrospira and anammox bacteria for shortcut nitrogen removal can drastically lower the carbon footprint of wastewater treatment facilities by decreasing aeration energy, carbon, alkalinity, and tank volume requirements while also potentially reducing nitrous oxide emissions. However, their co-occurrence as dominant nitrifying bacteria is rarely reported in full-scale wastewater treatment. As a result, there is a poor understanding of how operational parameters, in particular, dissolved oxygen, impact their activity and synergistic behavior. Here, we report the impact of dissolved oxygen concentration (DO = 2, 4, 6 mg/L) on the microbial community's transcriptomic expression in a full-scale integrated fixed film activated sludge (IFAS) municipal wastewater treatment facility where nitrogen removal is predominantly performed by comammox Nitrospira and anammox bacterial populations. 16S rRNA transcript compositions revealed anammox bacteria and Nitrospira were significantly more active in IFAS biofilms compared to suspended sludge biomass. In IFAS biofilms, anammox bacteria significantly increased hzo expression at lower dissolved oxygen concentrations and this increase was highly correlated with the amoA expression levels of comammox bacteria. Interestingly, the genes involved in nitrite oxidation by comammox bacteria were significantly more upregulated, relative to the genes involved in ammonia oxidation with decreasing dissolved oxygen concentrations. Ultimately, our findings suggest that comammox Nitrospira supplies anammox bacteria with nitrite via ammonia oxidation and that this synergistic behavior is dependent on dissolved oxygen concentrations.

Dentition patterns and molecular diversity of Mastophorus muris (Gmelin, 1790) (Nematoda: Spiruroidea) support a host-associated subdivision

Mastophorus muris (Gmelin, 1790) is a globally distributed parasitic nematode of broad range mammals. The taxonomy within the genus Mastophorus and the cryptic diversity among the genus are controversial among taxonomists. This study provides a detailed morphological description of M. muris from Mus musculus combined with a molecular phylogenetic approach. Moreover, descriptions and molecular data of M. muris from non-Mus rodents and wildcats complement our findings and together provide new insights into their taxonomy. The analysis of M. muris was based on light microscopy and scanning electron microscopy. The morphological description focused on the dentition pattern of the two trilobed pseudolabia. Additionally, we described the position of the vulva, arrangement of caudal pairs of papillae, spicules and measured specimens from both sexes and the eggs. For the molecular phylogenetic approach, we amplified the small subunit ribosomal RNA gene and the internal transcribed spacer, and the cytochrome c oxidase subunit 1. Mastophorus morphotypes based on dentition patterns and phylogenetic clustering indicate a subdivision of the genus in agreement with their host. We recognize two groups without a change to formal taxonomy: One group including those specimens infecting Mus musculus, and the second group including organisms infecting non-Mus rodents. Our genetic and morphological data shed light into the cryptic diversity within the genus Mastopohorus. We identified two host-associated groups of M. muris. The described morphotypes and genotypes of M. muris allow a consistent distinction between host-associated parasites.

Analysis of microbial dynamics in the soybean root-associated environments from community to single-cell levels

Plant root-associated environments such as the rhizosphere, rhizoplane, and endosphere, are notably different from non-root-associated soil environments. However, the microbial dynamics in these spatially divided compartments remain unexplored. In this study, we propose a combinational analysis of single-cell genomics with 16S rRNA gene sequencing. This method enabled us to understand the entire soil microbiome and individual root-associated microorganisms. We applied this method to soybean microbiomes and revealed that their composition was different between the rhizoplane and rhizosphere in the early growth stages, but became more similar as growth progressed. In addition, a total of 610 medium- to high-quality single-amplified genomes (SAGs) were acquired, including plant growth-promoting rhizobacteria (PGPR) candidates while genomes with high GC content tended to be missed by SAGs. The whole-genome analyses of the SAGs suggested that rhizoplane-enriched Flavobacterium solubilizes organophosphate actively and Bacillus colonizes roots more efficiently. Single-cell genomics, together with 16S rRNA gene sequencing, enabled us to connect microbial taxonomy and function, and assess microorganisms at a strain resolution even in the complex soil microbiome.

Evaluating the effects of mefenoxam on taxonomic and functional dynamics of nontarget fungal communities during carrot cultivation

Ridomil Gold SL (45.3% a.i. mefenoxam) is a widely used chemical fungicide for the control of oomycetes. However, its impact on fungal communities remains unexplored. Therefore, the goal of this study was to examine the effects of mefenoxam on the temporal dynamics of fungal taxonomic and functional diversities during carrot cultivation under four treatment groups: mefenoxam application with and without Pythium inoculation, and untreated control groups with and without Pythium inoculation. Our in vitro sensitivity assay showed that the maximum recommended concentration of mefenoxam, 0.24 ppm, did not suppress the mycelial growth of P. irregulare. At 100 ppm, mycelial growth was only reduced by 11.4%, indicating that the isolate was resistant to mefenoxam. MiSeq sequencing data revealed transient taxonomic variations among treatments 2 weeks post-treatment. Mortierella dominated the fungal community in the mefenoxam-Pythium combination treatment, as confirmed through PCR using our newly designed Mortierella-specific primers. Conversely, mefenoxam-Pythium combination had adverse effects on Penicillium, Trichoderma, and Fusarium, and decrease the overall alpha diversity. However, these compositional changes gradually reverted to those observed in the control by the 12th week. The predicted ecological functions of fungal communities in all Pythium and mefenoxam treatments shifted, leading to a decrease in symbiotrophs and plant pathogen functional groups. Moreover, the community-level physiological profiling approach, utilizing 96-well Biolog FF microplates, showed discernible variations in the utilization of 95 diverse carbon sources among the treatments. Notably, arbutin, L-arabinose, Tween 80, and succinamic acid demonstrated a strong positive association with Mortierella. Our findings demonstrate that a single application of mefenoxam at its recommended rate triggers substantial taxonomic and functional shifts in the soil fungal community. Considering this impact, the conventional agricultural practice of repeated mefenoxam application is likely to exert considerable shifts on the soil ecosystem that may affect agricultural sustainability.

Accurately clustering biological sequences in linear time by relatedness sorting

Clustering biological sequences into similar groups is an increasingly important task as the number of available sequences continues to grow exponentially. Search-based approaches to clustering scale super-linearly with the number of input sequences, making it impractical to cluster very large sets of sequences. Approaches to clustering sequences in linear time currently lack the accuracy of super-linear approaches. Here, I set out to develop and characterize a strategy for clustering with linear time complexity that retains the accuracy of less scalable approaches. The resulting algorithm, named Clusterize, sorts sequences by relatedness to linearize the clustering problem. Clusterize produces clusters with accuracy rivaling popular programs (CD-HIT, MMseqs2, and UCLUST) but exhibits linear asymptotic scalability. Clusterize generates higher accuracy and oftentimes much larger clusters than Linclust, a fast linear time clustering algorithm. I demonstrate the utility of Clusterize by accurately solving different clustering problems involving millions of nucleotide or protein sequences.

Whole-mitogenome analysis unveils previously undescribed genetic diversity in cane toads across their invasion trajectory

Invasive species offer insights into rapid adaptation to novel environments. The iconic cane toad (Rhinella marina) is an excellent model for studying rapid adaptation during invasion. Previous research using the mitochondrial NADH dehydrogenase 3 (ND3) gene in Hawai'ian and Australian invasive populations found a single haplotype, indicating an extreme genetic bottleneck following introduction. Nuclear genetic diversity also exhibited reductions across the genome in these two populations. Here, we investigated the mitochondrial genomics of cane toads across this invasion trajectory. We created the first reference mitochondrial genome for this species using long-read sequence data. We combined whole-genome resequencing data of 15 toads with published transcriptomic data of 125 individuals to construct nearly complete mitochondrial genomes from the native (French Guiana) and introduced (Hawai'i and Australia) ranges for population genomic analyses. In agreement with previous investigations of these populations, we identified genetic bottlenecks in both Hawai'ian and Australian introduced populations, alongside evidence of population expansion in the invasive ranges. Although mitochondrial genetic diversity in introduced populations was reduced, our results revealed that it had been underestimated: we identified 45 mitochondrial haplotypes in Hawai'ian and Australian samples, none of which were found in the native range. Additionally, we identified two distinct groups of haplotypes from the native range, separated by a minimum of 110 base pairs (0.6%). These findings enhance our understanding of how invasion has shaped the genetic landscape of this species.

Human metapneumovirus respiratory infection affects both innate and adaptive intestinal immunity

Introduction

Respiratory infections are one of the leading causes of morbidity and mortality worldwide, mainly in children, immunocompromised people, and the elderly. Several respiratory viruses can induce intestinal inflammation and alterations in intestinal microbiota composition. Human metapneumovirus (HMPV) is one of the major respiratory viruses contributing to infant mortality in children under 5 years of age worldwide, and the effect of this infection at the gut level has not been studied.

Methods

Here, we evaluated the distal effects of HMPV infection on intestinal microbiota and inflammation in a murine model, analyzing several post-infection times (days 1, 3, and 5). Six to eight-week-old C57BL/6 mice were infected intranasally with HMPV, and mice inoculated with a non-infectious supernatant (Mock) were used as a control group.

Results

We did not detect HMPV viral load in the intestine, but we observed significant changes in the transcription of IFN-γ in the colon, analyzed by qPCR, at day 1 post-infection as compared to the control group. Furthermore, we analyzed the frequencies of different innate and adaptive immune cells in the colonic lamina propria, using flow cytometry. The frequency of monocyte populations was altered in the colon of HMPV -infected mice at days 1 and 3, with no significant difference from control mice at day 5 post-infection. Moreover, colonic CD8+ T cells and memory precursor effector CD8+ T cells were significantly increased in HMPV-infected mice at day 5, suggesting that HMPV may also alter intestinal adaptive immunity. Additionally, we did not find alterations in antimicrobial peptide expression, the frequency of colonic IgA+ plasma cells, and levels of fecal IgA. Some minor alterations in the fecal microbiota composition of HMPV -infected mice were detected using 16s rRNA sequencing. However, no significant differences were found in β-diversity and relative abundance at the genus level.

Discussion

To our knowledge, this is the first report describing the alterations in intestinal immunity following respiratory infection with HMPV infection. These effects do not seem to be mediated by direct viral infection in the intestinal tract. Our results indicate that HMPV can affect colonic innate and adaptive immunity but does not significantly alter the microbiota composition, and further research is required to understand the mechanisms inducing these distal effects in the intestine.

Elevated methane flux in a tropical peatland post-fire is linked to depth-dependent changes in peat microbiome assembly

Fires in tropical peatlands extend to depth, transforming them from carbon sinks into methane sources and severely limit forest recovery. Peat microbiomes influence carbon transformations and forest recovery, yet our understanding of microbiome shifts post-fire is currently limited. Our previous study highlighted altered relationships between the peat surface, water table, aboveground vegetation, and methane flux after fire in a tropical peatland. Here, we link these changes to post-fire shifts in peat microbiome composition and assembly processes across depth. We report kingdom-specific and depth-dependent shifts in alpha diversity post-fire, with large differences at deeper depths. Conversely, we found shifts in microbiome composition across all depths. Compositional shifts extended to functional groups involved in methane turnover, with methanogens enriched and methanotrophs depleted at mid and deeper depths. Finally, we show that community shifts at deeper depths result from homogeneous selection associated with post-fire changes in hydrology and aboveground vegetation. Collectively, our findings provide a biological basis for previously reported methane fluxes after fire and offer new insights into depth-dependent shifts in microbiome assembly processes, which ultimately underlie ecosystem function predictability and ecosystem recovery.

Multiple sequence alignment-based RNA language model and its application to structural inference

Compared with proteins, DNA and RNA are more difficult languages to interpret because four-letter coded DNA/RNA sequences have less information content than 20-letter coded protein sequences. While BERT (Bidirectional Encoder Representations from Transformers)-like language models have been developed for RNA, they are ineffective at capturing the evolutionary information from homologous sequences because unlike proteins, RNA sequences are less conserved. Here, we have developed an unsupervised multiple sequence alignment-based RNA language model (RNA-MSM) by utilizing homologous sequences from an automatic pipeline, RNAcmap, as it can provide significantly more homologous sequences than manually annotated Rfam. We demonstrate that the resulting unsupervised, two-dimensional attention maps and one-dimensional embeddings from RNA-MSM contain structural information. In fact, they can be directly mapped with high accuracy to 2D base pairing probabilities and 1D solvent accessibilities, respectively. Further fine-tuning led to significantly improved performance on these two downstream tasks compared with existing state-of-the-art techniques including SPOT-RNA2 and RNAsnap2. By comparison, RNA-FM, a BERT-based RNA language model, performs worse than one-hot encoding with its embedding in base pair and solvent-accessible surface area prediction. We anticipate that the pre-trained RNA-MSM model can be fine-tuned on many other tasks related to RNA structure and function.

Sutterella and its metabolic pathways positively correlate with vaccine-elicited antibody responses in infant rhesus macaques

Introduction

It is becoming clearer that the microbiota helps drive responses to vaccines; however, little is known about the underlying mechanism. In this study, we aimed to identify microbial features that are associated with vaccine immunogenicity in infant rhesus macaques.

Methods

We analyzed 16S rRNA gene sequencing data of 215 fecal samples collected at multiple timepoints from 64 nursery-reared infant macaques that received various HIV vaccine regimens. PERMANOVA tests were performed to determine factors affecting composition of the gut microbiota throughout the first eight months of life in these monkeys. We used DESeq2 to identify differentially abundant bacterial taxa, PICRUSt2 to impute metagenomic information, and mass spectrophotometry to determine levels of fecal short-chain fatty acids and bile acids.

Results

Composition of the early-life gut microbial communities in nursery-reared rhesus macaques from the same animal care facility was driven by age, birth year, and vaccination status. We identified a Sutterella and a Rodentibacter species that positively correlated with vaccine-elicited antibody responses, with the Sutterella species exhibiting more robust findings. Analysis of Sutterella-related metagenomic data revealed five metabolic pathways that significantly correlated with improved antibody responses following HIV vaccination. Given these pathways have been associated with short-chain fatty acids and bile acids, we quantified the fecal concentration of these metabolites and found several that correlated with higher levels of HIV immunogen-elicited plasma IgG.

Discussion

Our findings highlight an intricate bidirectional relationship between the microbiota and vaccines, where multiple aspects of the vaccination regimen modulate the microbiota and specific microbial features facilitate vaccine responses. An improved understanding of this microbiota-vaccine interplay will help develop more effective vaccines, particularly those that are tailored for early life.

Draft genome sequencing of Naganishia species isolated from the polar environments

The draft genomes of five Naganishia strains were sequenced using MinION and annotated using Funannotate pipeline. Phylogenetic and genomic analyses were performed to provide their genetic relationships, diversity, and potential functional capabilities. This approach will aid in understanding their potential to survive under microgravity and their resilience to extreme environments.

Genomic characterization and radiation tolerance of Naganishia kalamii sp. nov. and Cystobasidium onofrii sp. nov. from Mars 2020 mission assembly facilities

During the construction and assembly of the Mars 2020 mission components at two different NASA cleanrooms, several fungal strains were isolated. Based on their colony morphology, two strains that showed yeast-like appearance were further characterized for their phylogenetic position. The species-level classification of these two novel strains, using traditional colony and cell morphology methods combined with the phylogenetic reconstructions using multi-locus sequence analysis (MLSA) based on several gene loci (ITS, LSU, SSU, RPB1, RPB2, CYTB and TEF1), and whole genome sequencing (WGS) was carried out. This polyphasic taxonomic approach supported the conclusion that the two basidiomycetous yeasts belong to hitherto undescribed species. The strain FJI-L2-BK-P3T, isolated from the Jet Propulsion Laboratory Spacecraft Assembly Facility, was placed in the Naganishia albida clade (Filobasidiales, Tremellomycetes), but is genetically and physiologically different from other members of the clade. Another yeast strain FKI-L6-BK-PAB1T, isolated from the Kennedy Space Center Payload Hazardous and Servicing Facility, was placed in the genus Cystobasidium (Cystobasidiales, Cystobasidiomycetes) and is distantly related to C. benthicum. Here we propose two novel species with the type strains, Naganishia kalamii sp. nov. (FJI-L2-BK-P3T = NRRL 64466 = DSM 115730) and Cystobasidium onofrii sp. nov. (FKI-L6-BK-PAB1T = NRRL 64426 = DSM 114625). The phylogenetic analyses revealed that single gene phylogenies (ITS or LSU) were not conclusive, and MLSA and WGS-based phylogenies were more advantageous for species discrimination in the two genera. The genomic analysis predicted proteins associated with dehydration and desiccation stress-response and the presence of genes that are directly related to osmotolerance and psychrotolerance in both novel yeasts described. Cells of these two newly-described yeasts were exposed to UV-C radiation and compared with N. onofrii, an extremophilic UV-C resistant cold-adapted Alpine yeast. Both novel species were UV resistant, emphasizing the need for collecting and characterizing extremotolerant microbes, including yeasts, to improve microbial reduction techniques used in NASA planetary protection programs.

Temporal pesticide dynamics alter specific eukaryotic taxa in a coastal transition zone

Land use change and anthropogenic forcing can drastically alter the rates and patterns of sediment transport and modify biodiversity and ecosystem functions in coastal transition zones, such as the coastal ecosystems. Molecular studies of sediment extracted DNAs provide information on currently living organisms within the upper layers or buried from various periods of time, but might also provide knowledge on species dynamics, replacement and turnover. In this study, we evaluated the eukaryotic communities of a marine core that present a shift in soil erosion that was linked to glyphosate usage and correlated to chlordecone resurgence since 2000. We show differences in community composition between samples from the second half of the last century and those from the last two decades. Temporal analyses of the relative abundance, alpha diversity, and beta diversity for the two periods demonstrated different temporal dynamics depending on the considered taxonomic group. In particular, Ascomycetes showed a decrease in abundance over the most recent period associated with changes in community membership but not community structure. Two photosynthetic groups, Bacillariophyceae and Prasinophytes clade VII, showed a different pattern with an increase in abundance since the beginning of the 21st century with a decrease in diversity and evenness to form more heterogeneous communities dominated by a few abundant OTUs. Altogether, our data reveal that agricultural usages such as pesticide use can have long-term and species-dependent implications for microeukaryotic coastal communities on a tropical island.

A real data-driven simulation strategy to select an imputation method for mixed-type trait data

Missing observations in trait datasets pose an obstacle for analyses in myriad biological disciplines. Considering the mixed results of imputation, the wide variety of available methods, and the varied structure of real trait datasets, a framework for selecting a suitable imputation method is advantageous. We invoked a real data-driven simulation strategy to select an imputation method for a given mixed-type (categorical, count, continuous) target dataset. Candidate methods included mean/mode imputation, k-nearest neighbour, random forests, and multivariate imputation by chained equations (MICE). Using a trait dataset of squamates (lizards and amphisbaenians; order: Squamata) as a target dataset, a complete-case dataset consisting of species with nearly complete information was formed for the imputation method selection. Missing data were induced by removing values from this dataset under different missingness mechanisms: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). For each method, combinations with and without phylogenetic information from single gene (nuclear and mitochondrial) or multigene trees were used to impute the missing values for five numerical and two categorical traits. The performances of the methods were evaluated under each missing mechanism by determining the mean squared error and proportion falsely classified rates for numerical and categorical traits, respectively. A random forest method supplemented with a nuclear-derived phylogeny resulted in the lowest error rates for the majority of traits, and this method was used to impute missing values in the original dataset. Data with imputed values better reflected the characteristics and distributions of the original data compared to complete-case data. However, caution should be taken when imputing trait data as phylogeny did not always improve performance for every trait and in every scenario. Ultimately, these results support the use of a real data-driven simulation strategy for selecting a suitable imputation method for a given mixed-type trait dataset.

Lymphoma cells lacking pro-apoptotic BAX are highly resistant to BH3-mimetics targeting pro-survival MCL-1 but retain sensitivity to conventional DNA-damaging drugs

BH3-mimetic drugs are an anti-cancer therapy that can induce apoptosis in malignant cells by directly binding and inhibiting pro-survival proteins of the BCL-2 family. The BH3-mimetic drug venetoclax, which targets BCL-2, has been approved for the treatment of chronic lymphocytic leukaemia and acute myeloid leukaemia by regulatory authorities worldwide. However, while most patients initially respond well, resistance and relapse while on this drug is an emerging and critical issue in the clinic. Though some studies have begun uncovering the factors involved in resistance to BCL-2-targeting BH3-mimetic drugs, little focus has been applied to pre-emptively tackle resistance for the next generation of BH3-mimetic drugs targeting MCL-1, which are now in clinical trials for diverse blood cancers. Therefore, using pre-clinical mouse and human models of aggressive lymphoma, we sought to predict factors likely to contribute to the development of resistance in patients receiving MCL-1-targeting BH3-mimetic drugs. First, we performed multiple whole genome CRISPR/Cas9 KO screens and identified that loss of the pro-apoptotic effector protein BAX, but not its close relative BAK, could confer resistance to MCL-1-targeting BH3-mimetic drugs in both short-term and long-term treatment regimens, even in lymphoma cells lacking the tumour suppressor TRP53. Furthermore, we found that mouse Eµ-Myc lymphoma cells selected for loss of BAX, as well as upregulation of the untargeted pro-survival BCL-2 family proteins BCL-XL and A1, when made naturally resistant to MCL-1 inhibitors by culturing them in increasing doses of drug over time, a situation mimicking the clinical application of these drugs. Finally, we identified therapeutic approaches which could overcome these two methods of resistance: the use of chemotherapeutic drugs or combined BH3-mimetic treatment, respectively. Collectively, these results uncover some key factors likely to cause resistance to MCL-1 inhibition in the clinic and suggest rational therapeutic strategies to overcome resistance that should be investigated further.

Gut microbiota variation between climatic zones and due to migration strategy in passerine birds

Introduction

Decreasing biotic diversity with increasing latitude is an almost universal macroecological pattern documented for a broad range of taxa, however, there have been few studies focused on changes in gut microbiota (GM) across climatic zones.

Methods

Using 16S rRNA amplicon profiling, we analyzed GM variation between temperate (Czechia) and tropical (Cameroon) populations of 99 passerine bird species and assessed GM similarity of temperate species migrating to tropical regions with that of residents/short-distance migrants and tropical residents. Our study also considered the possible influence of diet on GM.

Results

We observed no consistent GM diversity differences between tropical and temperate species. In the tropics, GM composition varied substantially between dry and rainy seasons and only a few taxa exhibited consistent differential abundance between tropical and temperate zones, irrespective of migration behavior and seasonal GM changes. During the breeding season, trans-Saharan migrant GM diverged little from species not overwintering in the tropics and did not show higher similarity to tropical passerines than temperate residents/short-distance migrants. Interestingly, GM of two temperate-breeding trans-Saharan migrants sampled in the tropical zone matched that of tropical residents and converged with other temperate species during the breeding season. Diet had a slight effect on GM composition of tropical species, but no effect on GM of temperate hosts.

Discussion

Consequently, our results demonstrate extensive passerine GM plasticity, the dominant role of environmental factors in its composition and limited effect of diet.

Low diversity and microdiversity of comammox bacteria in wastewater systems suggest specific adaptations within the Ca. Nitrospira nitrosa cluster

Studies have found Ca. Nitrospira nitrosa-like bacteria to be the principal or sole comammox bacteria in nitrogen removal systems for wastewater treatment. In contrast, multiple populations of strict ammonia and nitrite oxidizers co-exist in similar systems. This apparent lack of diversity is surprising and could impact the feasibility of leveraging comammox bacteria for nitrogen removal. We used full-length 16S rRNA gene sequencing and genome-resolved metagenomics to compare the species-level diversity of comammox bacteria with that of strict nitrifiers in full-scale wastewater treatment systems and assess whether this comparison is consistent or diverged at the strain-level. Full-length 16S rRNA gene sequencing indicated that Nitrosomonas-like bacteria exhibited higher species-level diversity in comparison with other nitrifying bacteria, while the strain-level diversity (also called microdiversity) of most Nitrospira-like bacteria were higher than Nitrosomonas-like bacteria with few exceptions (one Nitrospira lineage II population). Comammox bacterial metagenome assembled genomes (MAGs) were associated with Ca. Nitrospira nitrosa. The average amino acid identity between principal comammox bacterial MAGs (93% ± 3) across systems was significantly higher than that of the Nitrosomonas-like ammonia oxidizers (73% ± 8), the Nitrospira_A-like nitrite oxidizer (85% ± 4), and the Nitrospira_D-like nitrite oxidizer (83% ± 1). This demonstrated the low species-level diversity of comammox bacteria compared with strict nitrifiers and further suggests that the same comammox population was detected in all systems. Comammox bacteria (Nitrospira lineage II), Nitrosomonas and, Nitrospira_D (Nitrospira lineage II) MAGs were significantly less microdiverse than the Nitrospira_A (lineage I) MAGs. Interestingly, strain-resolved analysis also indicates that different nitrogen removal systems harbor different comammox bacterial strains within the Ca. Nitrospira nitrosa cluster. These results suggest that comammox bacteria associated with Ca. Nitrospira nitrosa have low species- and strain-level diversity in nitrogen removal systems and may thus harbor specific adaptations to the wastewater ecosystem.

Prokaryotes of renowned Karlovy Vary (Carlsbad) thermal springs: phylogenetic and cultivation analysis

BACKGROUND

The extreme conditions of thermal springs constitute a unique aquatic habitat characterized by low nutrient contents and the absence of human impacts on the microbial community composition. Thus, these springs may host phylogenetically novel microorganisms with potential use in biotechnology. With this hypothesis in mind, we examined the microbial composition of four thermal springs of the world-renowned spa town of Karlovy Vary (Carlsbad), Czechia, which differ in their temperature and chemical composition.

RESULTS

Microbial profiling using 16S rRNA gene sequencing revealed the presence of phylogenetically novel taxa at various taxonomic levels, spanning from genera to phyla. Many sequences belonged to novel classes within the phyla Hydrothermae, Altiarchaeota, Verrucomicrobia, and TA06. Cultivation-based methods employing oligotrophic media resulted in the isolation of 44 unique bacterial isolates. These include strains that withstand concentrations of up to 12% NaCl_w/v in cultivation media or survive a temperature of 100 °C, as well as hitherto uncultured bacterial species belonging to the genera Thermomonas, Paenibacillus, and Cellulomonas. These isolates harbored stress response genes that allow them to thrive in the extreme environment of thermal springs.

CONCLUSIONS

Our study is the first to analyze the overall microbial community composition of the renowned Karlovy Vary thermal springs. We provide insight into yet another level of uniqueness of these springs. In addition to their unique health benefits and cultural significance, we demonstrate that these springs harbor phylogenetically distinct microorganisms with unusual life strategies. Our findings open up avenues for future research with the promise of a deeper understanding of the metabolic potential of these microorganisms.

KnotAli: informed energy minimization through the use of evolutionary information

BACKGROUND

Improving the prediction of structures, especially those containing pseudoknots (structures with crossing base pairs) is an ongoing challenge. Homology-based methods utilize structural similarities within a family to predict the structure. However, their prediction is limited to the consensus structure, and by the quality of the alignment. Minimum free energy (MFE) based methods, on the other hand, do not rely on familial information and can predict structures of novel RNA molecules. Their prediction normally suffers from inaccuracies due to their underlying energy parameters.

RESULTS

We present a new method for prediction of RNA pseudoknotted secondary structures that combines the strengths of MFE prediction and alignment-based methods. KnotAli takes a multiple RNA sequence alignment as input and uses covariation and thermodynamic energy minimization to predict possibly pseudoknotted secondary structures for each individual sequence in the alignment. We compared KnotAli's performance to that of three other alignment-based programs, two that can handle pseudoknotted structures and one control, on a large data set of 3034 RNA sequences with varying lengths and levels of sequence conservation from 10 families with pseudoknotted and pseudoknot-free reference structures. We produced sequence alignments for each family using two well-known sequence aligners (MUSCLE and MAFFT).

CONCLUSIONS

We found KnotAli's performance to be superior in 6 of the 10 families for MUSCLE and 7 of the 10 for MAFFT. While both KnotAli and Cacofold use background noise correction strategies, we found KnotAli's predictions to be less dependent on the alignment quality. KnotAli can be found online at the Zenodo image: https://doi.org/10.5281/zenodo.5794719.

Variation in diet composition and its relation to gut microbiota in a passerine bird

Quality and quantity of food items consumed has a crucial effect on phenotypes. In addition to direct effects mediated by nutrient resources, an individual’s diet can also affect the phenotype indirectly by altering its gut microbiota, a potent modulator of physiological, immunity and cognitive functions. However, most of our knowledge of diet-microbiota interactions is based on mammalian species, whereas little is still known about these effects in other vertebrates. We developed a metabarcoding procedure based on cytochrome c oxidase I high-throughput amplicon sequencing and applied it to describe diet composition in breeding colonies of an insectivorous bird, the barn swallow (Hirundo rustica). To identify putative diet-microbiota associations, we integrated the resulting diet profiles with an existing dataset for faecal microbiota in the same individual. Consistent with previous studies based on macroscopic analysis of diet composition, we found that Diptera, Hemiptera, Coleoptera and Hymenoptera were the dominant dietary components in our population. We revealed pronounced variation in diet consumed during the breeding season, along with significant differences between nearby breeding colonies. In addition, we found no difference in diet composition between adults and juveniles. Finally, our data revealed a correlation between diet and faecal microbiota composition, even after statistical control for environmental factors affecting both diet and microbiota variation. Our study suggests that variation in diet induce slight but significant microbiota changes in a non-mammalian host relying on a narrow spectrum of items consumed.

FindNonCoding: rapid and simple detection of non-coding RNAs in genomes

SUMMARY

Non-coding RNAs are often neglected during genome annotation due to their difficulty of detection relative to protein coding genes. FindNonCoding takes a pattern mining approach to capture the essential sequence motifs and hairpin loops representing a non-coding RNA family and quickly identify matches in genomes. FindNonCoding was designed for ease of use and accurately finds non-coding RNAs with a low false discovery rate.

AVAILABILITY AND IMPLEMENTATION

FindNonCoding is implemented within the DECIPHER package (v2.19.3) for R (v4.1) available from Bioconductor. Pre-trained models of common non-coding RNA families are included for bacteria, archaea and eukarya.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Correlations Between the Metabolome and the Endophytic Fungal Metagenome Suggests Importance of Various Metabolite Classes in Community Assembly in Horseradish (Armoracia rusticana, Brassicaceae) Roots

The plant microbiome is an increasingly intensive research area, with significance in agriculture, general plant health, and production of bioactive natural products. Correlations between the fungal endophytic communities and plant chemistry can provide insight into these interactions, and suggest key contributors on both the chemical and fungal side. In this study, roots of various horseradish (Armoracia rusticana) accessions grown under the same conditions were sampled in two consecutive years and chemically characterized using a quality controlled, untargeted metabolomics approach by LC-ESI-MS/MS. Sinigrin, gluconasturtiin, glucoiberin, and glucobrassicin were also quantified. Thereafter, a subset of roots from eight accessions (n = 64) with considerable chemical variability was assessed for their endophytic fungal community, using an ITS2 amplicon-based metagenomic approach using a custom primer with high coverage on fungi, but no amplification of host internal transcribed spacer (ITS). A set of 335 chemical features, including putatively identified flavonoids, phospholipids, peptides, amino acid derivatives, indolic phytoalexins, a glucosinolate, and a glucosinolate downstream product was detected. Major taxa in horseradish roots belonged to Cantharellales, Glomerellales, Hypocreales, Pleosporales, Saccharomycetales, and Sordariales. Most abundant genera included typical endophytes such as Plectosphaerella, Thanatephorus, Podospora, Monosporascus, Exophiala, and Setophoma. A surprising dominance of single taxa was observed for many samples. In summary, 35.23% of reads of the plant endophytic fungal microbiome correlated with changes in the plant metabolome. While the concentration of flavonoid kaempferol glycosides positively correlated with the abundance of many fungal strains, many compounds showed negative correlations with fungi including indolic phytoalexins, a putative glucosinolate but not major glucosinolates and a glutathione isothiocyanate adduct. The latter is likely an in vivo glucosinolate decomposition product important in fungal arrest. Our results show the potency of the untargeted metabolomics approach in deciphering plant-microbe interactions and depicts a complex array of various metabolite classes in shaping the endophytic fungal community.

Current Technologies for RNA-Directed Liquid Diagnostics

There is unequivocal acceptance of the variety of enormous potential liquid nucleic acid-based diagnostics seems to offer. However, the existing controversies and the increased awareness of RNA-based techniques in society during the current global COVID-19 pandemic have made the readiness of liquid nucleic acid-based diagnostics for routine use a matter of concern. In this regard-and in the context of oncology-our review presented and discussed the status quo of RNA-based liquid diagnostics. We summarized the technical background of the available assays and benchmarked their applicability against each other. Herein, we compared the technology readiness level in the clinical context, economic aspects, implementation as part of routine point-of-care testing as well as performance power. Since the preventive care market is the most promising application sector, we also investigated whether the developments predominantly occur in the context of early disease detection or surveillance of therapy success. In addition, we provided a careful view on the current biotechnology investment activities in this sector to indicate the most attractive strategies for future economic success. Taken together, our review shall serve as a current reference, at the interplay of technology, clinical use and economic potential, to guide the interested readers in this rapid developing sector of precision medicine.

Development and implementation of a scalable and versatile test for COVID-19 diagnostics in rural communities

Rapid and widespread testing of severe acute respiratory coronavirus 2 (SARS-CoV-2) is essential for an effective public health response aimed at containing and mitigating the coronavirus disease 2019 (COVID-19) pandemic. Successful health policy implementation relies on early identification of infected individuals and extensive contact tracing. However, rural communities, where resources for testing are sparse or simply absent, face distinctive challenges to achieving this success. Accordingly, we report the development of an academic, public land grant University laboratory-based detection assay for the identification of SARS-CoV-2 in samples from various clinical specimens that can be readily deployed in areas where access to testing is limited. The test, which is a quantitative reverse transcription polymerase chain reaction (RT-qPCR)-based procedure, was validated on samples provided by the state laboratory and submitted for FDA Emergency Use Authorization. Our test exhibits comparable sensitivity and exceeds specificity and inclusivity values compared to other molecular assays. Additionally, this test can be re-configured to meet supply chain shortages, modified for scale up demands, and is amenable to several clinical specimens. Test development also involved 3D engineering critical supplies and formulating a stable collection media that allowed samples to be transported for hours over a dispersed rural region without the need for a cold-chain. These two elements that were critical when shortages impacted testing and when personnel needed to reach areas that were geographically isolated from the testing center. Overall, using a robust, easy-to-adapt methodology, we show that an academic laboratory can supplement COVID-19 testing needs and help local health departments assess and manage outbreaks. This additional testing capacity is particularly germane for smaller cities and rural regions that would otherwise be unable to meet the testing demand.

Fetal meconium does not have a detectable microbiota before birth

Microbial colonization of the human intestine impacts host metabolism and immunity; however, exactly when colonization occurs is unclear. Although many studies have reported bacterial DNA in first-pass meconium samples, these samples are typically collected hours to days after birth. Here, we investigated whether bacteria could be detected in meconium before birth. Fetal meconium (n = 20) was collected by rectal swab during elective breech caesarean deliveries without labour and before antibiotics and compared to technical and procedural controls (n = 5), first-pass meconium (neonatal meconium; n = 14) and infant stool (n = 25). Unlike first-pass meconium, no microbial signal distinct from negative controls was detected in fetal meconium by 16S ribosomal RNA gene sequencing. Additionally, positive aerobic (n = 10 of 20) and anaerobic (n = 12 of 20) clinical cultures of fetal meconium (13 of 20 samples positive in at least one culture) were identified as likely skin contaminants, most frequently Staphylococcus epidermidis, and not detected by sequencing in most samples (same genera detected by culture and sequencing in 2 of 13 samples with positive culture). We conclude that fetal gut colonization of healthy term infants does not occur before birth and that microbial profiles of neonatal meconium reflect populations acquired during and after birth.

Using a multiple-delivery-mode training approach to develop local capacity and infrastructure for advanced bioinformatics in Africa

With more microbiome studies being conducted by African-based research groups, there is an increasing demand for knowledge and skills in the design and analysis of microbiome studies and data. However, high-quality bioinformatics courses are often impeded by differences in computational environments, complicated software stacks, numerous dependencies, and versions of bioinformatics tools along with a lack of local computational infrastructure and expertise. To address this, H3ABioNet developed a 16S rRNA Microbiome Intermediate Bioinformatics Training course, extending its remote classroom model. The course was developed alongside experienced microbiome researchers, bioinformaticians, and systems administrators, who identified key topics to address. Development of containerised workflows has previously been undertaken by H3ABioNet, and Singularity containers were used here to enable the deployment of a standard replicable software stack across different hosting sites. The pilot ran successfully in 2019 across 23 sites registered in 11 African countries, with more than 200 participants formally enrolled and 106 volunteer staff for onsite support. The pulling, running, and testing of the containers, software, and analyses on various clusters were performed prior to the start of the course by hosting classrooms. The containers allowed the replication of analyses and results across all participating classrooms running a cluster and remained available posttraining ensuring analyses could be repeated on real data. Participants thus received the opportunity to analyse their own data, while local staff were trained and supported by experienced experts, increasing local capacity for ongoing research support. This provides a model for delivering topic-specific bioinformatics courses across Africa and other remote/low-resourced regions which overcomes barriers such as inadequate infrastructures, geographical distance, and access to expertise and educational materials.

aliFreeFoldMulti: alignment-free method to predict secondary structures of multiple RNA homologs

Predicting RNA structure is crucial for understanding RNA’s mechanism of action. Comparative approaches for the prediction of RNA structures can be classified into four main strategies. The three first—align-and-fold, align-then-fold and fold-then-align—exploit multiple sequence alignments to improve the accuracy of conserved RNA-structure prediction. Align-and-fold methods perform generally better, but are also typically slower than the other alignment-based methods. The fourth strategy—alignment-free—consists in predicting the conserved RNA structure without relying on sequence alignment. This strategy has the advantage of being the faster, while predicting accurate structures through the use of latent representations of the candidate structures for each sequence. This paper presents aliFreeFoldMulti, an extension of the aliFreeFold algorithm. This algorithm predicts a representative secondary structure of multiple RNA homologs by using a vector representation of their suboptimal structures. aliFreeFoldMulti improves on aliFreeFold by additionally computing the conserved structure for each sequence. aliFreeFoldMulti is assessed by comparing its prediction performance and time efficiency with a set of leading RNA-structure prediction methods. aliFreeFoldMulti has the lowest computing times and the highest maximum accuracy scores. It achieves comparable average structure prediction accuracy as other methods, except TurboFoldII which is the best in terms of average accuracy but with the highest computing times. We present aliFreeFoldMulti as an illustration of the potential of alignment-free approaches to provide fast and accurate RNA-structure prediction methods.