Tracking the microbial communities from the farm to the processing facility of a washed-rind cheese operation.

Milk residue and the accompanying biofilm accumulation in milking systems can compromise the microbial quality of milk and the downstream processes of cheese production. Over a six-month study, the microbial ecosystems of milk (n = 24), tap water (n = 24) and environmental swabs (n = 384) were cultured by plating decimal dilutions to obtain viable counts of total aerobic mesophilic lactose-utilizing bacteria (lactose-M17), lactic acid bacteria (MRS), yeasts and molds (Yeast, Glucose, Chloramphenicol (YGC) medium). Viable aerobic lactose-M17 plate counts of milk remained well below 4.7 log CFU/ml over five of the months, except for 1 week in November where milk at the facility exceeded 5 log CFU/ml. Swab samples of the farm milking equipment showed consistent viable counts after sanitation, while the bulk tank swabs contained the lowest counts. Viable counts from swabs of the facility were generally below the detection limit in the majority of samples with occasional residual contamination on some food contact surfaces. Extracted DNA was amplified using primers targeting the V3-V4 region of the 16S rRNA gene, and the amplicons were sequenced by MiSeq to determine the shared microbiota between the farm and the processing facility (8 genera). Culture independent analysis of bacterial taxa in milk, water and residual contamination after sanitation with swab samples revealed the shared and distinct microbiota between the sample types of both facilities. Amplicon sequence variants (ASVs) of the V3-V4 region of the 16S rRNA gene revealed that the microbiota of milk samples had lower diversity than water or environmental swabs (279 ASVs compared to 3,444 in water and 8,747 in environmental swabs). Brevibacterium and Yaniella (both Actinomycetota) were observed in all sampling types. Further studies will include whole genome sequencing of Brevibacterium spp. isolates to determine their functionality and diversity within the system.

Changes in the rhizosphere and root-associated bacteria community of white Guinea yam (Dioscorea rotundata Poir.) impacted by genotype and nitrogen fertilization.

The bacterial diversity and composition of water yam (Dioscorea alata L. cv. A-19), which can grow without chemical fertilization, have recently been characterized with no significant differences compared with the use of chemical fertilization. However, the diversity and community structure of bacteria associated with the white Guinea yam (Dioscorea rotundata), the most cultivated and economically important yam in West Africa, have not yet been investigated. This study characterized the bacterial diversity and composition associated with bulk soil, rhizosphere, and plant roots in six white Guinea yam genotypes (S004, S020, S032, S042, S058, and S074) in field experiments in Ibadan, Nigeria under N-based chemical fertilizer application. The largest diversity of bacteria was found in the bulk soil, followed by the rhizosphere and roots. Based on the alpha diversity analysis, the bacterial diversity in both S020 and S042 increased with fertilizer application among the bulk soil samples. S058 grown under no-fertilizer conditions had the highest bacterial diversity among the rhizosphere samples. Beta diversity analysis highlighted the significant difference in the composition of bacteria associated with the genotypes and fertilizer treatments, and S032 had a unique bacterial composition compared to the other genotypes. The dominant phylum across all sample types was Proteobacteria. Actinobacteriota was the dominant phylum among bulk soil samples. At the genus level, Bacillus was the most abundant bacterial genus across both the control and treated samples. Pseudomonas was predominant across all rhizosphere samples. Chryseobacterium, Sphingobium, Delftia and Klebsiella associated with the rhizosphere were shown the altered relative abundance between the control and treated samples depending on genotypes. A genus related to symbiotic nitrogen-fixing bacteria, the Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium clade, showed higher relative abundance among all root samples, indicating that it is a core bacterial genus. Furthermore, the field application of chemical fertilizer had a significant impact on the relative abundances of two genera related to symbiotic nitrogen-fixers, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium clade and Bradyrhizobium in the rhizosphere and root. These results suggest that N-based chemical fertilizers and plant genotypes would influence the compositional arrangement of associated bacterial communities, including symbiotic nitrogen-fixing bacteria.

The "Dry-Lab" Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data.

Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the "wet-lab" procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final "dry-lab" phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies' self-control in order to detect species substitution and counterfeit frauds.

Glycan Profile and Sequence Variants of Certified Ricin Reference Material and Other Ricin Samples Yield Unique Molecular Signature Features.

A certified reference material of ricin (CRM-LS-1) was produced by the EuroBioTox consortium to standardise the analysis of this biotoxin. This study established the N-glycan structures and proportions including their loci and occupancy of ricin CRM-LS-1. The glycan profile was compared with ricin from different preparations and other cultivars and isoforms. A total of 15 different oligomannosidic or paucimannosidic structures were identified in CRM-LS-1. Paucimannose was mainly found within the A-chain and oligomannose constituted the major glycan type of the B-chain. Furthermore, the novel primary structure variants E138 and D138 and four different C-termini of the A-chain as well as two B-chain variants V250 and F250 were elucidated. While the glycan proportions and loci were similar among all variants in CRM-LS-1 and ricin isoforms D and E of all cultivars analysed, a different stoichiometry for isoforms D and E and the amino acid variants were found. This detailed physicochemical characterization of ricin regarding the glycan profile and amino acid sequence variations yields unprecedented insight into the molecular features of this protein toxin. The variable attributes discovered within different cultivars present signature motifs and may allow discrimination of the biotoxin's origin that are important in molecular forensic profiling. In conclusion, our data of in-depth CRM-LS-1 characterization combined with the analysis of other cultivars is representative for known ricin variants.

Swarm and UNOISE outperform DADA2 and Deblur for denoising high-diversity marine seafloor samples.

The performance of sequence variant resolution analytic tools for metabarcoding has not yet been adequately benchmarked for high-diversity environmental samples. We therefore evaluated the sequence variant tools DADA2, Deblur, Swarm, and UNOISE, using high-diversity seafloor samples, resulting in comparisons of 1800 sequence variant tables. The evaluation was based on 30 sediment grab samples, for which 3 replica samples were collected. Each replica sample was extracted using 5 common DNA extraction kits, resulting in 450 DNA extracts which were 16S rRNA gene sequenced (V3-V4), using Illumina. Assessments included variation across replica samples, extraction kits, and denoising methods, in addition to applying prior knowledge about alpha diversity correlations toward the cosmopolitan marine archaeon Nitrosopumilus with high diversity and the sulfide oxidizing Sulfurovum with low diversity. DADA2 displayed the highest variance between replicates (Manhattan distance 1.14), while Swarm showed the lowest variance (Manhattan distance 0.93). For the analysis based on prior biological knowledge, UNOISE displayed the highest alpha diversity (Simpson's D) correlation toward Nitrosopumilus (Spearman rho = 0.85), while DADA2 showed the lowest (Spearman rho = 0.10). Deblur completely eliminated Nitrosopumilus from the dataset. For Sulfurovum, on the other hand, all the methods showed comparable results. In conclusion, our evaluations show that Swarm and UNOISE performed better than DADA2 and Deblur for high-diversity seafloor samples.

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches.

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

eDNA metabarcoding reveals biodiversity and depth stratification patterns of dinoflagellate assemblages within the epipelagic zone of the western Coral Sea.

BACKGROUND: Dinoflagellates play critical roles in the functioning of marine ecosystems but also may pose a hazard to human and ecosystem health by causing harmful algal blooms (HABs). The Coral Sea is a biodiversity hotspot, but its dinoflagellate assemblages in pelagic waters have not been studied by modern sequencing methods. We used metabarcoding of the 18 S rRNA V4 amplicon to assess the diversity and structure of dinoflagellate assemblages throughout the water column to a depth of 150 m at three stations in the Western Coral Sea. Additionally, at one station we compared metabarcoding with morphological methods to optimise identification and detection of dinoflagellates. RESULTS: Stratification of dinoflagellate assemblages was evident in depth-specific relative abundances of taxonomic groups; the greatest difference was between the 5-30 m assemblages and the 130-150 m assemblages. The relative abundance of Dinophyceae (photosynthetic and heterotrophic) decreased with increasing depth, whereas that of Syndiniales (parasitic) increased with increasing depth. The composition of major taxonomic groups was similar among stations. Taxonomic richness and diversity of amplicon sequence variants (ASVs) were similar among depths and stations; however, the abundance of dominant taxa was highest within 0-30 m, and the abundance of rare taxa was highest within 130-150 m, indicating adaptations to specific depth strata. The number of unclassified ASVs at the family and species levels was very high, particularly for Syndinian representatives. CONCLUSIONS: Dinoflagellate assemblages in open water of the Coral Sea are highly diverse and taxonomically stratified by depth; patterns of relative abundance along the depth gradient reflect environmental factors and ecological processes. Metabarcoding detects more species richness than does traditional microscopical methods of sample analysis, yet the methods are complementary, with morphological analysis revealing additional richness. The large number of unclassified dinoflagellate-ASVs indicates a need for improved taxonomic reference databases and suggests presence of dinoflagellate-crypto and-morphospecies.

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows.

BACKGROUND: Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. RESULTS: In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits` genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets` high effect. CONCLUSION: Our results confirm the connection of milk production and health traits in dairy cattle via the animals` metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits` connection in more detail.

Exploring the biological diversity and source species of medicinal horseflies through metabarcoding.

Horseflies from the Tabanidae family play a significant role in traditional Chinese medicine to treat various health conditions, including coronary heart disease, stroke, headaches, liver cirrhosis, psoriasis, and hepatic carcinoma. There are 27 species of Tabaninae (Tabanidae) used as medicine, and they showed high morphological similarities with those for which medicinal properties have not been reported. Nonetheless, there have been reports suggesting that medicinal crude drugs sometimes contain irrelevant or false species, impacting the drug's efficacy. In this current study, we collected 14 batches, totaling 13,528 individuals, from various provinces in China. Instead of "classic" DNA barcoding strategy, we employed a high-throughput metabarcoding approach to assess the biological composition of crude drug mixtures derived from horseflies. Our analysis identified 40 Amplicon Sequence Variants (ASVs) with similarity percentages ranging from 92% to 100% with 12 previously reported species. Species delimitation methods revealed the presence of 11 Molecular Operational Taxonomic Units (MOTUs), with ten belonging to the Tabanus genus and one to Hybomitra. Tabanus sp6 displayed the highest relative abundance, and its ASVs showed close resemblance to Tabanus pleski. Our investigations revealed that the medicinal batches were biologically composed of 6 to 12 species. Some batches contained ASVs that closely resembled species previously associated with false Tabanus species. In conclusion, our findings offer valuable insights into the biological composition of crude drugs derived from horseflies and have the potential to enhance the quality of these traditional medicines.

Diversity of potential nitrogen-fixing bacteria from rhizosphere of the Coffea arabica L. and Coffea canephora L.

Coffea arabica L. and Coffea canephora L. are coffee species most consumed and marketed in the world. The coffee crop requires a large amount of nitrogen, which shows the importance of knowledge of the population of nitrogen-fixing bacteria (NFB) from the rhizosphere of these crops. These microorganisms may help the reduction of nitrogen fertilizing. However, there is no production of NFB inoculum in the coffee. Therefore, our objective was to evaluate the diversity of potential nitrogen-fixing bacteria (PNFB) in the rhizosphere of C. arabica and C. canephora. The microbial DNA of the soil was extracted, amplified through PCR, and sequenced at the Illumina Miseq. platform. The PNFB prediction was performed using the program PICRUSt2. Three hundred and thirty-seven amplicon sequence variants (ASVs) were identified as PNFB in two coffee species. Xanthobacteraceae, Rhizobium multhospitiium, Rhizobium mesosinicum, and Bradyrhizobium sp. were detected in all samples and main components of the core microbiota of the coffee plant rhizosphere. Some ASVs are exclusive from one of the coffee farms, showing that the coffee specie cultivated may influence the PNFB communities. However, edaphoclimatic factors and soil chemical attributes can also influence the distribution of ASVs in coffee soil. In the C. canephora, the PNFB diversity was influenced by the altitude and the soil chemical attributes, while the altitude and the phosphorus content influenced the PNFB population in C. arabica. Our results are important to the understanding of the PNFB dynamic in coffee soil and for the agricultural inputs bioprospecting to coffee.

Sequence variants in the BTD underlying biotinidase deficiency in families of Pakistani origin.

BACKGROUND: Biotinidase deficiency (BTD) is a rare autosomal recessive metabolic disease, which develops neurological symptoms because of the impaired biotin recycling. Pathogenic mutations on BTD gene cause BTD deficiency. The clinical features and mutation analysis of Pakistani children with BTD deficiency have rarely been described. Herein, for the first time, we report the clinical features, BTD gene mutations and biochemical analysis of seven symptomatic children with BTD deficiency from Pakistan. METHODS: Seven suspected BTD-deficient patients who presented abnormal organic acid profiles and clinical features were subjected to Sanger sequencing to identify pathogenic mutations in the BTD gene. The results were analyzed by Mutation Surveyor Software. RESULTS: All seven patients exhibited common biotinidase deficiency symptoms including hypotonia, developmental delay and seizures. Biochemical analysis shows marked excretion of 3-hydroxy isovalerate in all cases, followed by 3-hydroxy propionate and methyl citrate. Sanger sequencing revealed one frame-shift mutation, c.98_104delinsTCC (p.Cys33Phefs), and two missense mutations, c.1612C>A (p.Arg538Ser) and c.1330G>C (p.Asp444His). All mutations were in the homozygous state and classified as pathogenic in published studies and mutation databases. CONCLUSIONS: This study has validated the BTD variants as the underlying cause of biotinidase deficiency in which molecular testing of BTD is supported by urinary organic acid analysis and clinical diagnosis. Secondly, the strength of the local availability of this test in Pakistan will paved the way for the neonatal screening of biotinidase deficiency.

Sequence Variants in the WNT10B Underlying Non-Syndromic Split-Hand/Foot Malformation.

Introduction: Split hand and foot malformation (SHFM) or ectrodactyly is a rare limb deformity characterized by median cleft of the hand and foot with impaired or missing central rays. It can occur as an isolated anomaly or in association with abnormalities of other body parts. Methods: After delineating the clinical features of two families (A-B), with non-syndromic SHFM, exome and Sanger sequencing were employed to search for the disease-causing variants. Results: Analysis of exome and Sanger sequencing data revealed two causative variants in the WNT10B gene in affected members of the two families. This included a novel missense change [c.338G>C; p.(Gly113Ala)] in family A and a previously reported frameshift variant [c.884-896delTCCAGCCCCGTCT; p.(Phe295Cysfs*87)] in family B. Conclusion: Our findings add a novel variant in WNT10B gene as the underlying cause of SHFM. The finding adds to the growing body of knowledge about the genetic basis of developmental disorders and provides valuable insights into the molecular mechanisms that regulate limb development.

Unbiased discovery of natural sequence variants that influence fungal virulence.

Isolates of Cryptococcus neoformans, a fungal pathogen that kills over 112,000 people each year, differ from a 19-Mb reference genome at a few thousand up to almost a million DNA sequence positions. We used bulked segregant analysis and association analysis, genetic methods that require no prior knowledge of sequence function, to address the key question of which naturally occurring sequence variants influence fungal virulence. We identified a region containing such variants, prioritized them, and engineered strains to test our findings in a mouse model of infection. At one locus, we identified a 4-nt variant in the PDE2 gene that occurs in common laboratory strains and severely truncates the encoded phosphodiesterase. The resulting loss of phosphodiesterase activity significantly impacts virulence. Our studies demonstrate a powerful and unbiased strategy for identifying key genomic regions in the absence of prior information and provide significant sequence and strain resources to the community.

Diversities in Leigh Syndrome Associated with MT-ATP6 Gene Variants.

INTRODUCTION: Leigh syndrome (LS) is clinically and genetically heterogeneous and presents defective mitochondrial bioenergetics. Patients present neurological symptoms and imagiological features that may result in early death [1]. The LS has been associated with mitochondrial DNA (mtDNA) variants, e.g., m.8993T>G (L156R) and m.8993T>C (L156P), in the MT-ATP6 gene. They lead to the substitution of a highly conserved amino acid in subunit 6 of ATP synthase, affecting the F0 domain and ATP synthesis [1-3]. We present five cases with m.8993T>G and a family harbouring m.8993T>C+m.1555A>G (proband and four relatives). METHODS: Our laboratory received 48 samples from LS-suspected patients. The samples (various tissues) were assessed for bioenergetics (activity of mitochondrial respiratory chain (MRC) complexes, ubiquinone content) and genetic analyses (mtDNA copy number, Sequencing and PCR-RFLP) by established protocols. RESULTS/CASE REPORT: Bioenergetics were assessed in 5 patients (various tissues) with varying levels of MRC/ATP synthase impairment. Six cases had a mtDNA pathogenic variant in the 8993 nucleotide associated with LS. Five cases presented the m.8993T>G variant, one of which (P5) possibly de novo. This variant was homoplasmy (P1-3) or very high heteroplasmy (P4/5, 90-95%). Of the four patients with bioenergetics assessment, three (P1/3/4) had deficiencies of MRC complexes, and P5 had small deficits. The other case (familial, proband and 4 relatives) presented a combination of m.1555A>G (homoplasmy) and m.8993T>C (heteroplasmy) variants. The proband presents m.8993T>C in 95% heteroplasmy and 85-35% in three relatives. All have m.1555A>G in homoplasmy, including the fourth relative without m.8993T>C. A deficiency (31%) was found in complex V activity in muscle for proband. CONCLUSION: We present a case series of patients harbouring pathogenic variants in the 8993 nucleotide of mtDNA, which have been associated with LS and impairment of MRC's complex V. These cases highlight the variability in clinical symptoms and their severity, as well as genetic heterogeneity within LS. Many patients will not present a classic pathogenic variant and there are many cases of asymptomatic relatives (carriers). It is important to get a broader view of the cases - classical methods and multiple tissue analysis are still valuable tools for the comprehensive characterization of patients.

Comparative effect of acid and heat inoculum pretreatment on dark fermentative biohydrogen production.

This study delves into the impact of various pretreatment methods on the inoculum in dark fermentation trials, specifically exploring thermal shock at different temperatures (60, 80, and 100 °C) and durations (15, 30, and 60 min), as well as acid shock at pH 5.5. Initial acidification of the substrate/inoculum mixture facilitates H2 generation, making acid shock an effective pretreatment option. However, it is also observed that combining thermal and acid pretreatments boosts H2 production synergistically. The synergy between thermal and acid pretreatments results in a significant improvement, increasing the overall hydrogen production efficiency by more than 9% compared to assays involving acidification alone. This highlights the considerable potential for optimizing pretreatment strategies. Furthermore, the study sheds light on the critical role of inoculum characteristics in the process, with diverse hydrogen-generating bacteria significantly influencing outcomes. The established equivalent performance of HCl and H2SO4 in inoculum pretreatment demonstrates the versatility of these acids in shaping the microbial community and influencing hydrogen production. The analysis of glucose conversion data highlights a prevalence of butyric acid in all trials, irrespective of the pretreatment method, emphasizing the dominance of the butyrate pathway in hydrogen generation. Additionally, an examination of the microbial community offers valuable insights into the intricate relationships between temperature, pH, and microbial diversity. Bacteroidota established its dominance among the bacterial populations, with a relative abundance exceeding 20-25% in the raw inoculum, and this dominance further increased following the treatment. Thermal and acid pretreatments result in significant shifts in dominant microbial communities, with some non-dominant phyla like Cloacimonadota and Spirochaetota becoming more prominent. These shifts in microbial diversity underscore the sensitivity of microbial communities to environmental conditions and pretreatment methods, further highlighting the importance of understanding their dynamics in dark fermentation processes.

Machine learning strategy for identifying altered gut microbiomes for diagnostic screening in myasthenia gravis.

Myasthenia gravis (MG) is a neuromuscular junction disease with a complex pathophysiology and clinical variation for which no clear biomarker has been discovered. We hypothesized that because changes in gut microbiome composition often occur in autoimmune diseases, the gut microbiome structures of patients with MG would differ from those without, and supervised machine learning (ML) analysis strategy could be trained using data from gut microbiota for diagnostic screening of MG. Genomic DNA from the stool samples of MG and those without were collected and established a sequencing library by constructing amplicon sequence variants (ASVs) and completing taxonomic classification of each representative DNA sequence. Four ML methods, namely least absolute shrinkage and selection operator, extreme gradient boosting (XGBoost), random forest, and classification and regression trees with nested leave-one-out cross-validation were trained using ASV taxon-based data and full ASV-based data to identify key ASVs in each data set. The results revealed XGBoost to have the best predicted performance. Overlapping key features extracted when XGBoost was trained using the full ASV-based and ASV taxon-based data were identified, and 31 high-importance ASVs (HIASVs) were obtained, assigned importance scores, and ranked. The most significant difference observed was in the abundance of bacteria in the Lachnospiraceae and Ruminococcaceae families. The 31 HIASVs were used to train the XGBoost algorithm to differentiate individuals with and without MG. The model had high diagnostic classification power and could accurately predict and identify patients with MG. In addition, the abundance of Lachnospiraceae was associated with limb weakness severity. In this study, we discovered that the composition of gut microbiomes differed between MG and non-MG subjects. In addition, the proposed XGBoost model trained using 31 HIASVs had the most favorable performance with respect to analyzing gut microbiomes. These HIASVs selected by the ML model may serve as biomarkers for clinical use and mechanistic study in the future. Our proposed ML model can identify several taxonomic markers and effectively discriminate patients with MG from those without with a high accuracy, the ML strategy can be applied as a benchmark to conduct noninvasive screening of MG.

The review of genetic screening services and common BRCA1/2 variants among South African breast cancer patients.

The South African genetic screening services for breast cancer comprise targeted and comprehensive tests that screen for the presence of genetic alterations. Clinically, these variants determine the risk of disease development as well as treatment approaches best suited for carriers. The current targeted tests screen for seven pathogenic sequence variants, which are mainly common among Whites, a population that constitutes 9.1% of South Africa. However, these tests are offered to all patients despite consistent negative results observed among Blacks, Indians, and Mixed ancestry (known as Coloreds in South Africa). Consequently, Blacks, White, and Colored patients who potentially carry other variants receive unbefitting treatment, resulting in poor clinical response, recurrence, and high mortality. This review aimed to identify the presence and incidence of pathogenic variants in BRCA1/2 previously reported in all South African populations. We selected literature using a scoping review approach, from which we included eight articles and two reports. Overall, we identified 59 BRCA1 and 60 BRCA2 pathogenic sequence variants from a cohort of 5709 patients and unknown patients from 90 families. The most reported variant was BRCA2 c.7943delG, which was common in White and Colored patients. None of the seven common variants was reported in either Blacks or Indians, which demonstrates the urgency to tailor genetic tests which are optimal for all South African patients and present a range of variants which could serve as diagnostic targets for Black, Indian, and Colored patients.

A mixed-model approach for estimating drivers of microbiota community composition and differential taxonomic abundance.

Next-generation sequencing (NGS) and metabarcoding approaches are increasingly applied to wild animal populations, but there is a disconnect between the widely applied generalized linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology typically applied to metabarcoding data. Here, we describe the suitability of a novel GLMM-based approach for analyzing the taxon-specific sequence read counts derived from standard metabarcoding data. This approach allows decomposition of the contribution of different drivers to variation in community composition (e.g., age, season, individual) via interaction terms in the model random-effects structure. We provide guidance to implementing this approach and show how these models can identify how responsible specific taxonomic groups are for the effects attributed to different drivers. We applied this approach to two cross-sectional data sets from the Soay sheep population of St. Kilda. GLMMs showed agreement with dissimilarity-based approaches highlighting the substantial contribution of age and minimal contribution of season to microbiota community compositions, and simultaneously estimated the contribution of other technical and biological factors. We further used model predictions to show that age effects were principally due to increases in taxa of the phylum Bacteroidetes and declines in taxa of the phylum Firmicutes. This approach offers a powerful means for understanding the influence of drivers of community structure derived from metabarcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate contributions of additional factors such as host or microbe phylogeny to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities. IMPORTANCE NGS and fecal metabarcoding methods have provided powerful opportunities to study the wild gut microbiome. A wealth of data is, therefore, amassing across wild systems, generating the need for analytical approaches that can appropriately investigate simultaneous factors at the host and environmental scale that determine the composition of these communities. Here, we describe a generalized linear mixed-effects model (GLMM) approach to analyze read count data from metabarcoding of the gut microbiota, allowing us to quantify the contributions of multiple host and environmental factors to within-host community structure. Our approach provides outputs that are familiar to a majority of field ecologists and can be run using any standard mixed-effects modeling packages. We illustrate this approach using two metabarcoding data sets from the Soay sheep population of St. Kilda investigating age and season effects as worked examples.

Honey bees and bumble bees occupying the same landscape have distinct gut microbiomes and amplicon sequence variant-level responses to infections.

The gut microbiome of bees is vital for the health of their hosts. Given the ecosystem functions performed by bees, and the declines faced by many species, it is important to improve our understanding of the amount of natural variation in the gut microbiome, the level of sharing of bacteria among co-occurring species (including between native and non-native species), and how gut communities respond to infections. We conducted 16S rRNA metabarcoding to discern the level of microbiome similarity between honey bees (Apis mellifera, N = 49) and bumble bees (Bombus spp., N = 66) in a suburban-rural landscape. We identified a total of 233 amplicon sequence variants (ASVs) and found simple gut microbiomes dominated by bacterial taxa belonging to Gilliamella, Snodgrassella, and Lactobacillus. The average number of ASVs per species ranged from 4.00-15.00 (8.79 ± 3.84, mean ± SD). Amplicon sequence variant of one bacterial species, G. apicola (ASV 1), was widely shared across honey bees and bumble bees. However, we detected another ASV of G. apicola that was either exclusive to honey bees, or represented an intra-genomic 16S rRNA haplotype variant in honey bees. Other than ASV 1, honey bees and bumble bees rarely share gut bacteria, even ones likely derived from outside environments (e.g., Rhizobium spp., Fructobacillus spp.). Honey bee bacterial microbiomes exhibited higher alpha diversity but lower beta and gamma diversities than those of bumble bees, likely a result of the former possessing larger, perennial hives. Finally, we identified pathogenic or symbiotic bacteria (G. apicola, Acinetobacter sp. and Pluralibacter sp.) that associate with Trypanosome and/or Vairimorpha infections in bees. Such insights help to determine bees' susceptibility to infections should gut microbiomes become disrupted by chemical pollutants and contribute to our understanding of what constitutes a state of dysbiosis.

Identification of IKZF1 genetic mutations as new molecular subtypes in acute myeloid leukaemia.

BACKGROUND: Genetic mutations of IKZF1 have been frequently delineated in B-lineage acute leukaemia (B-ALL) but rarely elucidated in acute myeloid leukaemia (AML). IKZF1 mutations confer a poor prognosis in AML, and hotspot mutations of IKZF1, N159Y and N159S tend to occur in B-ALL and AML respectively. However, the pathogenesis of IKZF1 N159S in AML and IKZF1 lineage susceptibility are largely unknown. METHODS: The genetic and clinical characteristics of IKZF1-mutated AML patients were evaluated. Multi-omics analysis and functional assays were performed in vitro using IKZF1 mutations knock-in AML cell lines. RESULTS: 23 (4.84%) small sequence variants of IKZF1 were identified in 475 newly diagnosed AML (non-M3) patients. Based on RNA sequencing, three classes of IKZF1-related AML were defined, including 9 patients (39.13%) with IKZF1 N159S mutations, 10 (43.47%) with CEBPA mutations and 4 others (17.39%). IKZF1 N159S may define a unique subgroup with higher HOXA/B expression and native B-cell immune fractions. Gene expression data of multiple knock-in cell lines indicate that the lymphocyte differentiation-related MME and CD44 kept high expression in IKZF1 N159Y but were downregulated in N159S. CUT&TAG sequencing showed that IKZF1 N159S reshaped the binding profiles of IKZF1. Integration analysis suggested that the pathogenesis of IKZF1 N159S may depend on the deregulation of several cofactors, such as oncogenic MYC and CPNE7 targets. CONCLUSIONS: Collectively, we dissected the molecular spectrum and clinical features of IKZF1-related AML, which may promote an in-depth understanding of the pathogenesis, lineage susceptibility and clinical research of AML.