Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes

Seasonal dynamics and environmental drivers of tissue and mucus microbiomes in the staghorn coral Acropora pulchra

Background

Rainfall-induced coastal runoff represents an important environmental impact in near-shore coral reefs that may affect coral-associated bacterial microbiomes. Shifts in microbiome community composition and function can stress corals and ultimately cause mortality and reef declines. Impacts of environmental stress may be site specific and differ between coral microbiome compartments (e.g., tissue versus mucus). Coastal runoff and associated water pollution represent a major stressor for near-shore reef-ecosystems in Guam, Micronesia.

Methods

Acropora pulchra colonies growing on the West Hagåtña reef flat in Guam were sampled over a period of 8 months spanning the 2021 wet and dry seasons. To examine bacterial microbiome diversity and composition, samples of A. pulchra tissue and mucus were collected during late April, early July, late September, and at the end of December. Samples were collected from populations in two different habitat zones, near the reef crest (farshore) and close to shore (nearshore). Seawater samples were collected during the same time period to evaluate microbiome dynamics of the waters surrounding coral colonies. Tissue, mucus, and seawater microbiomes were characterized using 16S DNA metabarcoding in conjunction with Illumina sequencing. In addition, water samples were collected to determine fecal indicator bacteria (FIB) concentrations as an indicator of water pollution. Water temperatures were recorded using data loggers and precipitation data obtained from a nearby rain gauge. The correlation structure of environmental parameters (temperature and rainfall), FIB concentrations, and A. pulchra microbiome diversity was evaluated using a structural equation model. Beta diversity analyses were used to investigate spatio-temporal trends of microbiome composition.

Results

Acropora pulchra microbiome diversity differed between tissues and mucus, with mucus microbiome diversity being similar to the surrounding seawater. Rainfall and associated fluctuations of FIB concentrations were correlated with changes in tissue and mucus microbiomes, indicating their role as drivers of A. pulchra microbiome diversity. A. pulchra tissue microbiome composition remained relatively stable throughout dry and wet seasons; tissues were dominated by Endozoicomonadaceae, coral endosymbionts and putative indicators of coral health. In nearshore A. pulchra tissue microbiomes, Simkaniaceae, putative obligate coral endosymbionts, were more abundant than in A. pulchra colonies growing near the reef crest (farshore). A. pulchra mucus microbiomes were more diverse during the wet season than the dry season, a distinction that was also associated with drastic shifts in microbiome composition. This study highlights the seasonal dynamics of coral microbiomes and demonstrates that microbiome diversity and composition may differ between coral tissues and the surface mucus layer.

Airborne microorganisms and key environmental factors shaping their community patterns in the core production area of the Maotai-flavor Baijiu

Airborne microorganisms are important parts of the Moutai-flavor Baijiu brewing microbial community, which directly affects the quality of Baijiu. However, environmental factors usually shape airborne microbiomes in different distilleries, even in the different production areas of the same distillery. Unfortunately, current understanding of environmental factors shaping airborne microbiomes in distilleries is very limited. To bridge this gap, we compared airborne microbiomes in the Moutai-flavor Baijiu core production areas of different distilleries in the Chishui River Basin and systematically investigated the key environmental factors that shape the airborne microbiomes. The top abundant bacterial communities are mainly affiliated to the phyla Actinobacteriota, Firmicutes, and Proteobacteri, whereas Ascomycota and Basidiomycota are the predominant fungal communities. The Random Forest analysis indicated that the biomarkers in three distilleries are Saccharomonospora and Bacillus, Thermoactinomyces, Oceanobacillus, and Methylobacterium, which are the core functional flora contributing to the production of Daqu. The correlation and network analyses showed that the distillery age and environmental temperature have a strong regulatory effect on airborne microbiomes, suggesting that the fermentation environment has a domesticating effect on air microbiomes. Our findings will greatly help us understand the relationship between airborne microbiomes and environmental factors in distilleries and support the production of the high-quality Moutai-flavor Baijiu.

Gut dysbiosis in patients with chronic pain: a systematic review and meta-analysis

Introduction

Recent evidence supports the contribution of gut microbiota dysbiosis to the pathophysiology of rheumatic diseases, neuropathic pain, and neurodegenerative disorders. The bidirectional gut-brain communication network and the occurrence of chronic pain both involve contributions of the autonomic nervous system and the hypothalamic pituitary adrenal axis. Nevertheless, the current understanding of the association between gut microbiota and chronic pain is still not clear. Therefore, the aim of this study is to systematically evaluate the existing knowledge about gut microbiota alterations in chronic pain conditions.

Methods

Four databases were consulted for this systematic literature review: PubMed, Web of Science, Scopus, and Embase. The Newcastle-Ottawa Scale was used to assess the risk of bias. The study protocol was prospectively registered at the International prospective register of systematic reviews (PROSPERO, CRD42023430115). Alpha-diversity, β-diversity, and relative abundance at different taxonomic levels were summarized qualitatively, and quantitatively if possible.

Results

The initial database search identified a total of 3544 unique studies, of which 21 studies were eventually included in the systematic review and 11 in the meta-analysis. Decreases in alpha-diversity were revealed in chronic pain patients compared to controls for several metrics: observed species (SMD= -0.201, 95% CI from -0.04 to -0.36, p=0.01), Shannon index (SMD= -0.27, 95% CI from -0.11 to -0.43, p<0.001), and faith phylogenetic diversity (SMD -0.35, 95% CI from -0.08 to -0.61, p=0.01). Inconsistent results were revealed for beta-diversity. A decrease in the relative abundance of the Lachnospiraceae family, genus Faecalibacterium and Roseburia, and species of Faecalibacterium prausnitzii and Odoribacter splanchnicus, as well as an increase in Eggerthella spp., was revealed in chronic pain patients compared to controls.

Discussion

Indications for gut microbiota dysbiosis were revealed in chronic pain patients, with non-specific disease alterations of microbes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023430115.

Responses of a soil fungal community to severe windstorm damages in an old silver fir stand

Forests are increasingly threatened by climate change and the Anthropocene seems to have favored the emergence and adaptation of pathogens. Robust monitoring methods are required to prevent biodiversity and ecosystems losses, and this imposes the choice of bioindicators of habitat health. Fungal communities are increasingly recognized as fundamental components in nearly all natural and artificial environments, and their ecosystem services have a huge impact in maintaining and restoring the functionality of ecosystems. We coupled metabarcoding and soil analyses to infer the dynamics of a fungal community inhabiting the old silver fir stand in Vallombrosa (Italy), which is known to be afflicted by both Armillaria and Annosum root rot. The forest was affected in 2015, by a windstorm which caused a partial falling and uprooting of trees. The remaining stand, not affected by the windstorm, was used as a comparison to infer the consequences of the ecosystem disturbance. We demonstrated that the abundance of pathogens alone is not able to explain the soil fungal differences shown by the two areas. The fungal community as a whole was equally rich in the two areas, even if a reduction of the core ectomycorrhizal mycobiome was observed in the wind-damaged area, accompanied by the increase of wood saprotrophs and arbuscular mycorrhizas. We hypothesize a reshaping of the fungal community and a potentially ongoing re-generation of its functionalities. Our hypothesis is driven by the evidence that key symbiotic, endophytic, and saprotrophic guilds are still present and diversified in the wind-damaged area, and that dominance of single taxa or biodiversity loss was not observed from a mycological point of view. With the present study, we aim at providing evidence that fungal communities are fundamental for the monitoring and the conservation of threatened forest ecosystems.

GREENER principles for environmentally sustainable computational science

The carbon footprint of scientific computing is substantial, but environmentally sustainable computational science (ESCS) is a nascent field with many opportunities to thrive. To realize the immense green opportunities and continued, yet sustainable, growth of computer science, we must take a coordinated approach to our current challenges, including greater awareness and transparency, improved estimation and wider reporting of environmental impacts. Here, we present a snapshot of where ESCS stands today and introduce the GREENER set of principles, as well as guidance for best practices moving forward.

Evaluation of the representative of using rumen fluid samples from lambs fed pelleted TMR for analysis of prokaryotic communities

The pelleted TMR pulverized the grass during processing, which may result in more solid attached microorganisms in the filtered rumen fluid. The objective of this study was evaluating the necessity of distinguishing physical phases of rumen contents for analysis of prokaryotes communities in rumen of lambs fed pelleted TMR, considering the dissimilarity of diversity and community of bacteria and archaea between fluid and mixed rumen contents. The yield of microbial DNA, bacterial diversity, abundances of fibrolytic bacteria of phylum Fibrobacterota and Spirochaetota, as well as genus Ruminococcus, Lachnospiraceae_NK3A20, Fibrobacter, and F082, and abundance of archaeal Methanimicrococcus in rumen fluid were lower than those in mixed phase of rumen contents (p ≤ 0.05). In conclusion, it is necessary to consider rumen content physical phases when studying the prokaryotic community in rumen of lambs fed pelleted TMR.

Changes in Oral Microbial Diversity in a Piglet Model of Traumatic Brain Injury

Dynamic changes in the oral microbiome have gained attention due to their potential diagnostic role in neurological diseases such as Alzheimer's disease and Parkinson's disease. Traumatic brain injury (TBI) is a leading cause of death and disability in the United States, but no studies have examined the changes in oral microbiome during the acute stage of TBI using a clinically translational pig model. Crossbred piglets (4-5 weeks old, male) underwent either a controlled cortical impact (TBI, n = 6) or sham surgery (sham, n = 6). The oral microbiome parameters were quantified from the upper and lower gingiva, both buccal mucosa, and floor of the mouth pre-surgery and 1, 3, and 7 days post-surgery (PS) using the 16S rRNA gene. Faith's phylogenetic diversity was significantly lower in the TBI piglets at 7 days PS compared to those of sham, and beta diversity at 1, 3, and 7 days PS was significantly different between TBI and sham piglets. However, no significant changes in the taxonomic composition of the oral microbiome were observed following TBI compared to sham. Further studies are needed to investigate the potential diagnostic role of the oral microbiome during the chronic stage of TBI with a larger number of subjects.

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.