A comprehensive workflow for optimizing RNA-seq data analysis.

BACKGROUND: Current RNA-seq analysis software for RNA-seq data tends to use similar parameters across different species without considering species-specific differences. However, the suitability and accuracy of these tools may vary when analyzing data from different species, such as humans, animals, plants, fungi, and bacteria. For most laboratory researchers lacking a background in information science, determining how to construct an analysis workflow that meets their specific needs from the array of complex analytical tools available poses a significant challenge. RESULTS: By utilizing RNA-seq data from plants, animals, and fungi, it was observed that different analytical tools demonstrate some variations in performance when applied to different species. A comprehensive experiment was conducted specifically for analyzing plant pathogenic fungal data, focusing on differential gene analysis as the ultimate goal. In this study, 288 pipelines using different tools were applied to analyze five fungal RNA-seq datasets, and the performance of their results was evaluated based on simulation. This led to the establishment of a relatively universal and superior fungal RNA-seq analysis pipeline that can serve as a reference, and certain standards for selecting analysis tools were derived for reference. Additionally, we compared various tools for alternative splicing analysis. The results based on simulated data indicated that rMATS remained the optimal choice, although consideration could be given to supplementing with tools such as SpliceWiz. CONCLUSION: The experimental results demonstrate that, in comparison to the default software parameter configurations, the analysis combination results after tuning can provide more accurate biological insights. It is beneficial to carefully select suitable analysis software based on the data, rather than indiscriminately choosing tools, in order to achieve high-quality analysis results more efficiently.

Brain functional activity-based classification of autism spectrum disorder using an attention-based graph neural network combined with gene expression.

Autism spectrum disorder (ASD) is a complex brain neurodevelopmental disorder related to brain activity and genetics. Most of the ASD diagnostic models perform feature selection at the group level without considering individualized information. Evidence has shown the unique topology of the individual brain has a fundamental impact on brain diseases. Thus, a data-constructing method fusing individual topological information and a corresponding classification model is crucial in ASD diagnosis and biomarker discovery. In this work, we trained an attention-based graph neural network (GNN) to perform the ASD diagnosis with the fusion of graph data. The results achieved an accuracy of 79.78%. Moreover, we found the model paid high attention to brain regions mainly involved in the social-brain circuit, default-mode network, and sensory perception network. Furthermore, by analyzing the covariation between functional magnetic resonance imaging data and gene expression, current studies detected several ASD-related genes (i.e. MUTYH, AADAT, and MAP2), and further revealed their links to image biomarkers. Our work demonstrated that the ASD diagnostic framework based on graph data and attention-based GNN could be an effective tool for ASD diagnosis. The identified functional features with high attention values may serve as imaging biomarkers for ASD.

The establishment of a multiplex fluorescent polymerase chain reaction coupled with capillary electrophoresis analysis technology enables the simultaneous detection of 16 genotypes of human papillomavirus.

BACKGROUND: The detection and accurate genotyping of human papillomavirus (HPV) infection is critical for preventing and effectively treating cervical cancer. METHODS: A multiplex fluorescent polymerase chain reaction (PCR) coupled with a capillary electrophoresis method was developed for the simultaneous detection of the 16 most prevalent HPV genotypes. Twenty-five pairs of primers were ultimately selected to ensure that both E and L regions of nine HPV genotypes, as well as the E regions of seven HPV genotypes could be accurately amplified. RESULTS: This method enables the simultaneous detection and differentiation of 16 HPV genotypes in a single closed-tube reaction, accurately distinguishing products with molecular weight differences >1 bp through capillary electrophoresis. This method demonstrated exceptional accuracy, specificity, and repeatability with a detection limit of 10 copies/µL for all 16 HPV genotypes. Furthermore, 152 cervical swab specimens were obtained to compare the disparities between this approach and Cobas 4800 HPV detection method. The concordance rate and κ value were 90.1% and 0.802, respectively, indicating a high level of agreement. The established detection method was successfully applied to cervical swab specimens for determining HPV genotypes across all levels of cervical lesions, HPV52, 56, 16, and 59 were found to be most prevalent with infection rates of 10.8%, 9.1%, 6.5%, and 6.2%, respectively. CONCLUSIONS: This study has successfully established a detection method capable of simultaneously identifying 16 HPV genotypes. This approach can be further applied to HPV vaccine research and surveillance, with the potential for broad applications.

Identification of proteolytic bacteria from Yunnan fermented foods and their use to reduce the allergenicity of ß-lactoglobulin.

Beta-lactoglobulin (ß-LG) is considered to be the major allergenic protein in milk. Lactic acid bacteria (LAB) possess a protein hydrolysis system that holds great promise for hydrolyzing ß-LG and reducing its allergenicity. Therefore, this study aimed to screen LAB with ß-LG hydrolysis activity from Yunnan traditional fermented foods. The results showed that Pediococcus pentosaceus C1001, Pediococcus acidilactici E1601-1, and Lactobacillus paracasei E1601-2, could effectively hydrolyze ß-LG and further reduce its sensitization (more than 40%). All 3 lactic acid bacteria hydrolyzed ß-LG allergenic fragments V41-K60 and L149-I162. Moreover, they encode a variety of genes related to proteolysis, such as aminopeptidase pepC and pepN, proline peptidase pepIP and endopeptidase pepO, and L. paracasei E1601-2 contains extracellular protease coding gene prtP. And they encode a variety of genes associated with hydrolyzed proteins. The 3 strains screened in this study can be used to develop hypoallergenic dairy products.

Differential Gene Expression Analysis of Human Ovarian Follicular Cumulus and Mural Granulosa Cells Under the Influence of Insulin in IVF Ovulatory Women and Polycystic Ovary Syndrome Patients Through Network Analysis.

BACKGROUND: Polycystic ovarian syndrome (PCOS) is a commonly occurring reproductive disorder among the reproductive-aged women. Its global occurrence varies based on diagnostic guidelines, ethnicities, and locations of concern. Insulin resistance (IR) is commonly observed around 65-70% of women diagnosed with PCOS, representing a prevalent association. Consequently, the study was designed with an objective of illustrating the effect of insulin on mural and cumulus granulosa cells (GCs) of PCOS patients in comparison to normal ovulating women. METHODOLOGY: This study is a case-control design, wherein a total of 80 participants were recruited meeting criterion of inclusion and exclusion, divided into 8 groups with each group consisting of 10 samples. The process involves the isolation and culturing of mural granulosa cells (MGC) and cumulus granulosa cells (CGC) with and without exposure to insulin. The proteins released by untreated GCs and insulin-treated GCs were extracted, and complex protein mixtures were digested with trypsin, followed by tandem mass spectrometry analysis and data processing using bioinformatics. RESULTS: We found 595 proteins in both control and PCOS samples, of which 310 were contributed by MGCs and 285 by CGCs. The PCOS MGCs expressed 20%, both the normal MGCs and CGCs have equal representation of 16% by each, whereas the PCOS CGCs proteins contributed 15% of the total of the proteomic expression. However, the poor expression observed with the Insulin exposure, the Insulin treated PCOS CGCs contributes 13%, PCOS MGCs contributes 8%. The normal MGCs upon the Insulin treatment give 8% then and there only 4% of proteins expressed by normal CGCs after Insulin treatment. The Venn analysis widened on their precise expression topographies. The examination of strings exhibited important protein-protein interaction pathways. CONCLUSION: This is a pioneering investigation aimed to establish the link between hyperinsulinemia in localized follicular GCs and PCOS mechanisms by comparing them to control group. The examination of various attributes, mechanisms, and traits shown by genes and proteins in individuals with PCOS compared to control populations, alongside the investigation of the dynamics of these genes and proteins following exposure to insulin, holds promise for the formulation of novel hypotheses and strategies in the identification of new biomarkers.

Antibiotic-Resistance Profiles and Genetic Diversity of Shigella Isolates in China: Implications for Control Strategies.

The urgent need for comprehensive and systematic analyses of Shigella as the key pathogen led us to meticulously explore the epidemiology and molecular attributes of Shigella isolates. Accordingly, we procured 24 isolates (10 from Xinjiang and 14 from Wuhan, China) and performed serotype identification and antimicrobial susceptibility testing. Resistance gene detection and homology analysis by polymerase chain reaction and pulsed-field gel electrophoresis (PFGE), respectively, were performed for genetic diversity analysis. All isolates were identified as Shigella flexneri, with 70% (35.4-91.9%) and 30% (8.1-64.6%) of the Xinjiang isolates and 85.7% (56.2-97.5%) and 14.3% (2/14, 2.5-43.9%) of the Wuhan isolates belonging to serotype 2a and serotype 2b, respectively. All isolates displayed resistance to at least two antibiotics and complete resistance to ampicillin. Multidrug resistance (MDR) was recorded in 70.8% (48.8-86.6%) of isolates, with Xinjiang isolates exhibiting relatively higher resistance to ampicillin-sulbactam, piperacillin, ceftriaxone, and aztreonam. Conversely, Wuhan isolates displayed higher MDR and resistance to tetracycline, ciprofloxacin, levofloxacin, and cefepime relative to Xinjiang isolates. Molecular scrutiny of antibiotic-resistance determinants revealed that blaTEM was the main mechanism of ampicillin resistance, blaCTX-M was the main gene for resistance to third- and fourth-generation cephalosporins, and tetB was the predominant gene associated with tetracycline resistance. Four Xinjiang and seven Wuhan isolates shared T1-clone types (>85%), and two Xinjiang and one Wuhan isolates were derived from the T6 clone with a high similarity of 87%. Six PFGE patterns (T1, T2, T5, T6-3, T8, and T10) of S. flexneri were associated with MDR. Thus, there is a critical need for robust surveillance and control strategies in managing Shigella infections, along with the development of targeted interventions and antimicrobial stewardship programs tailored to the distinct characteristics of Shigella isolates in different regions of China.

Genome-Wide Transcriptomic and Metabolomic Analyses Unveiling the Defence Mechanisms of Populus tremula against Sucking and Chewing Insect Herbivores.

Plants and insects coevolved as an evolutionarily successful and enduring association. The molecular arms race led to evolutionary novelties regarding unique mechanisms of defence and detoxification in plants and insects. While insects adopt mechanisms to conquer host defence, trees develop well-orchestrated and species-specific defence strategies against insect herbivory. However, current knowledge on the molecular underpinnings of fine-tuned tree defence responses against different herbivore insects is still restricted. In the current study, using a multi-omics approach, we unveiled the defence response of Populus tremula against aphids (Chaitophorus populialbae) and spongy moths (Lymantria dispar) herbivory. Comparative differential gene expression (DGE) analyses revealed that around 272 and 1203 transcripts were differentially regulated in P. tremula after moth and aphid herbivory compared to uninfested controls. Interestingly, 5716 transcripts were differentially regulated in P. tremula between aphids and moth infestation. Further investigation showed that defence-related stress hormones and their lipid precursors, transcription factors, and signalling molecules were over-expressed, whereas the growth-related counterparts were suppressed in P. tremula after aphid and moth herbivory. Metabolomics analysis documented that around 37% of all significantly abundant metabolites were associated with biochemical pathways related to tree growth and defence. However, the metabolic profiles of aphid and moth-fed trees were quite distinct, indicating species-specific response optimization. After identifying the suitable reference genes in P. tremula, the omics data were further validated using RT-qPCR. Nevertheless, our findings documented species-specific fine-tuning of the defence response of P. tremula, showing conservation on resource allocation for defence overgrowth under aphid and moth herbivory. Such findings can be exploited to enhance our current understanding of molecular orchestration of tree responses against herbivory and aid in developing insect pest resistance P. tremula varieties.

Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment.

BACKGROUND: Previous studies have demonstrated that high-density lipoprotein cholesterol (HDL-C) plays an anti-atherosclerosis role through reverse cholesterol transport. Several studies have validated the efficacy and safety of natural products in treating atherosclerosis (AS). However, the study of raising HDL-C levels through natural products to treat AS still needs to be explored. METHODS: The gene sets associated with AS were collected and identified by differential gene analysis and database query. By constructing a protein-protein interaction (PPI) network, the core submodules in the network are screened out. At the same time, by calculating node importance (Nim) in the PPI network of AS disease and combining it with Kyoto Encyclopedia of genes and genomes (KEGG) pathways enrichment analysis, the key target proteins of AS were obtained. Molecular docking is used to screen out small natural drug molecules with potential therapeutic effects. By constructing an in vitro foam cell model, the effects of small molecules on lipid metabolism and key target expression of foam cells were investigated. RESULTS: By differential gene analysis, 451 differential genes were obtained, and a total of 313 disease genes were obtained from 6 kind of databases, then 758 AS-related genes were obtained. The enrichment analysis of the KEGG pathway showed that the enhancement of HDL-C level against AS was related to Lipid and atherosclerosis, Cholesterol metabolism, Fluid shear stress and atherosclerosis, PPAR signaling pathway, and other pathways. Then we intersected 31 genes in the core module of the PPI network, the top 30 genes in Nims, and 32 genes in the cholesterol metabolism pathway, and finally found 3 genes. After the above analysis and literature collection, we focused on the following three related gene targets: APOA1, LIPC, and CETP. Molecular docking showed that Genistein has a good binding affinity for APOA1, CETP, and LIPC. In vitro, experiments showed that Genistein can up-regulated APOA1, LIPC, and CETP levels. CONCLUSIONS: Based on our research, Genistein may have the effects of regulating HDL-C and anti-atherosclerosis. Its mechanism of action may be related to the regulation of LIPC, CETP, and APOA1 to improve lipid metabolism.

Climate warming has direct and indirect effects on microbes associated with carbon cycling in northern lakes.

Northern lakes disproportionately influence the global carbon cycle, and may do so more in the future depending on how their microbial communities respond to climate warming. Microbial communities can change because of the direct effects of climate warming on their metabolism and the indirect effects of climate warming on groundwater connectivity from thawing of surrounding permafrost, especially at lower landscape positions. Here we used shotgun metagenomics to compare the taxonomic and functional gene composition of sediment microbes in 19 peatland lakes across a 1600-km permafrost transect in boreal western Canada. We found microbes responded differently to the loss of regional permafrost cover than to increases in local groundwater connectivity. These results suggest that both the direct and indirect effects of climate warming, which were respectively associated with loss of permafrost and subsequent changes in groundwater connectivity interact to change microbial composition and function. Archaeal methanogens and genes involved in all major methanogenesis pathways were more abundant in warmer regions with less permafrost, but higher groundwater connectivity partly offset these effects. Bacterial community composition and methanotrophy genes did not vary with regional permafrost cover, and the latter changed similarly to methanogenesis with groundwater connectivity. Finally, we found an increase in sugar utilization genes in regions with less permafrost, which may further fuel methanogenesis. These results provide the microbial mechanism for observed increases in methane emissions associated with loss of permafrost cover in this region and suggest that future emissions will primarily be controlled by archaeal methanogens over methanotrophic bacteria as northern lakes warm. Our study more generally suggests that future predictions of aquatic carbon cycling will be improved by considering how climate warming exerts both direct effects associated with regional-scale permafrost thaw and indirect effects associated with local hydrology.

Silvimonas soli sp. nov., a new member of Chromobacteriaceae isolated from soil in Norrbyskär island, Sweden.

A novel bacterial species is described that was isolated from the soil of Norrbyskär island (Sweden). This Gram-negative, facultatively anaerobic and motile rod, designated 17-6T, was classified in the family Chromobacteriaceae, class Betaproteobacteria, and further characterized by a polyphasic approach. Comparative 16S rRNA gene analysis revealed the potential species novelty of the strain, with Silvimonas terrae (98.20 % similarity) and Silvimonas amylolytica (98.13 %) being its closest type strains. The phylogenetic novelty of the isolate at the level of species was confirmed using phylogenetic analyses based on the whole genome: average nucleotide identity values ranged from 79 to 81 %, average amino acid identity values from 75 to 81 % and percentage of conserved proteins values from 69-81 % with the members of genera Silvimonas and Amantichitinum. On the basis of phenotypic, phylogenetic, functional and genotypic analyses, we propose the isolate as the type strain of a novel species within the genus Silvimonas with the designation Silvimonas soli 17-6T (=DSM 115342T=CCM 9308T).

First Insights into the Bacterial Diversity of Mount Etna Volcanic Caves.

While microbial communities in limestone caves across the world are relatively understood, knowledge of the microbial composition in lava tubes is lagging behind. These caves are found in volcanic regions worldwide and are typically lined with multicolored microbial mats on their walls and ceilings. The Mount Etna (Sicily, S-Italy) represents one of the most active volcanos in the world. Due to its outstanding biodiversity and geological features, it was declared Natural Heritage of Humanity by the UNESCO in 2013. Despite the presence of more than 200 basaltic lava tubes, the microbial diversity of these hypogean systems has never been investigated so far. Here, we investigated bacterial communities in four lava tubes of Mount Etna volcano. Field emission scanning electron microscopy (FESEM) was carried out for the morphological characterization and detection of microbial features. We documented an abundant presence of microbial cells with different morphotypes including rod-shaped, filamentous, and coccoidal cells with surface appendages, resembling actinobacteria reported in other lava tubes across the world. Based on 16S rRNA gene analysis, the colored microbial mats collected were mostly composed of bacteria belonging to the phyla Actinomycetota, Pseudomonadota, Acidobacteriota, Chloroflexota, and Cyanobacteria. At the genus level, the analysis revealed a dominance of the genus Crossiella, which is actively involved in biomineralization processes, followed by Pseudomonas, Bacillus, Chujaibacter, and Sphingomonas. The presence of these taxa is associated with the carbon, nitrogen, and ammonia cycles, and some are possibly related to the anthropic disturbance of these caves. This study provides the first insight into the microbial diversity of the Etna volcano lava tubes, and expands on previous research on microbiology of volcanic caves across the world.

Identification of antisense and sense RNAs of intracrine fibroblast growth factor components as novel biomarkers in colorectal cancer and in silico studies for drug and nanodrug repurposing.

INTRODUCTION: Colorectal cancer (CRC) is one of the most malignant tumors and in which various efforts for screening is inconclusive.The intracrine FGF panel, the non-tyrosine kinase receptors (NTKR) FGFs and affiliated antisenses play a pivotal role in FGF signaling.The expression levels of coding and non-coding intracrine FGFs were assessed in CRC donors.Also, substantial costs and slow pace of drug discovery give high attraction to repurpose of previously discovered drugs to new opportunities. OBJECTIVES: The aim of present study was to evaluate the potential role of the coding and non-coding intracrine FGFs as a new biomarkers for CRC cases and defining drug repurposing to alleviate FGF down regulation. METHODS: RNA-seq data of colon adenocarcinomas (COAD) was downloaded using TCGA biolinks package in R.The DrugBank database (https://go.drugbank.com/) was used to extract interactions between drugs and candidate genes. A total of 200 CRC patients with detailed criteria were enrolled.RNAs were extracted with TRIzol-based protocol and amplified via LightCycler® instrument.FGF11 and FGF13 proteins validation was performed by used of immunohistochemistry technique in tumor and non-tumoral samples.Pearson's correlation analysis and ROC curve plotted by Prism 8.0 software. RESULTS: RNA-seq data from TCGA was analyzed by normalizing with edgeR.Differentially expressed gene (DEG) analysis was generated. WCC algorithm extracted the most significant genes with a total of 47 genes. Expression elevation of iFGF antisenses (12AS,13As,14AS) compared with the normal colon tissue were observed (P = 0.0003,P = 0.042,P = 0.026, respectively). Moreover,a significant decrease in expression of the corresponding sense iFGF genes was detected (P < 0.0001).Plotted receiver operating characteristic (ROC) curves for iFGF components' expression showed an area of over 0.70 (FGF11-13: 0.71% and FGF12-14: 0.78%, P < 0.001) for sense mRNA expression, with the highest sensitivity for FGF12 (92.8%) and lowest for FGF11 (61.41%).The artificial intelligence (AI) revealed the valproic acid as a repurposing drug to relief the down regulation of FGF12 and 13 in CRC patients. CONCLUSION: Intracrine FGFs panel was down regulated versus up regulation of dependent antisenses. Thus, developing novel biomarkers based on iFGF can be considered as a promising strategy for CRC screening.In advanced, valporic acid detected by AI as a repurposing drug which may be applied in clinical trials for CRC treatment.

SMAD4 variants and its genotype-phenotype correlations to juvenile polyposis syndrome.

BACKGROUND: Juvenile polyposis syndrome (JPS), a rare autosomal dominant syndrome, affects one per 100 000 births, increasing lifetime cancer risk by 9 - 50%. Around 40-60% of JPS cases are caused by disease-causing variants (DCV) in SMAD4 or BMPR1A genes, of which SMAD4 accounts for 20-30%. OBJECTIVES: To characterise genotype-phenotype correlations between sites and types of variants within SMAD4 to JPS phenotypes, to inform diagnosis, screening, and management of JPS. SEARCH METHODS: Online search databases utilised included Ovid MEDLINE, Embase Classic + Embase and PubMed, using search terms classified by MeSH on Demand. Adjacency operators, word truncation and Boolean operators were employed. 110 articles were included in the review, collating 291 variants from the literature. RESULTS: In SMAD4 + JPS patients, most variants are located around SMAD4's MH2 domain (3' end). Extracolonic involvement, massive gastric polyposis and a more aggressive phenotype have been associated with SMAD4 + JPS, predisposing to gastric cancer. This has contributed to an overall higher incidence of GI cancers compared to other genes causing JPS, with DCVs mostly all within the MH2 domain. Genetically related allelic disorders of SMAD4 also have variants in this region, including hereditary haemorrhagic telangiectasia (HHT) alongside SMAD4 + JPS, and Myhre syndrome, independent of JPS. Similarly, with DCVs in the MH2 domain, Ménétrier's disease, hypertrophic osteoarthropathy and juvenile idiopathic arthritis have been seen in this population, whereas cardiac pathologies have occurred both alongside and independently of SMAD4 + JPS with DCVs in the MH1 domain. CONCLUSION: Truncating and missense variants around the MH2 region of SMAD4 are most prevalent and pathogenic, thus should undergo careful surveillance. Given association with extracolonic polyposis and higher GI cancer risk, endoscopic screening should occur more frequently and at an earlier age in SMAD4 + JPS patients than in patients with other causative genes, with consideration of Ménétrier's disease on upper GI endoscopy. In addition, HHT should be evaluated within 6 months of diagnosis, alongside targeted clinical examination for extraintestinal manifestations associated with SMAD4 + JPS. This review may help modify clinical diagnosis and management of SMAD4 + JPS patients, and aid pathogenicity classification for SMAD4 DCVs through a better understanding of the phenotypes.

Nitrogen dynamics and biological processes in soil amended with microalgae grown in abattoir digestate to recover nutrients.

The use of microalgae for nutrient recovery from wastewater and subsequent conversion of the harvested biomass into fertilizers offers a sustainable approach towards creating a circular economy. Nonetheless, the process of drying the harvested microalgae represents an additional cost, and its impact on soil nutrient cycling compared to wet algal biomass is not thoroughly understood. To investigate this, a 56-day soil incubation experiment was conducted to compare the effects of wet and dried Scenedesmus sp. microalgae on soil chemistry, microbial biomass, CO2 respiration, and bacterial community diversity. The experiment also included control treatments with glucose, glucose + ammonium nitrate, and no fertilizer addition. The Illumina Mi-Seq platform was used to profile the bacterial community and in-silico analysis was performed to assess the functional genes involved in N and C cycling processes. The maximum CO2 respiration and microbial biomass carbon (MBC) concentration of dried microalgae treatment were 17% and 38% higher than those of paste microalgae treatment, respectively. NH4+ and NO3- released slowly and through decomposition of microalgae by soil microorganisms as compared to synthetic fertilizer control. The results indicate that heterotrophic nitrification may contribute to nitrate production for both microalgae amendments, as evidenced by low amoA gene abundance and a decrease in ammonium with an increase in nitrate concentration. Additionally, dissimilatory nitrate reduction to ammonium (DNRA) may be contributing to ammonium production in the wet microalgae amendment, as indicated by an increase in nrfA gene and ammonium concentration. This is a significant finding because DNRA leads to N retention in agricultural soils instead of N loss via nitrification and denitrification. Thus, further processing the microalgae through drying or dewetting may not be favorable for fertilizer production as the wet microalgae appeared to promote DNRA and N retention.

Using single-cell multi-omics screening of human fetal pancreas to identify novel players in human beta cell development.

Islet transplantation from organ donors can considerably improve glucose homeostasis and well-being in individuals with type 1 diabetes, where the beta cells are destroyed by the autoimmune attack, but there are insufficient donor islets to make this a widespread therapy. Strategies are therefore being developed to generate unlimited amounts of insulin-producing beta cells from pluripotent stem cells, with the aim that they will be transplanted to treat diabetes. Whilst much progress has been made in recent years in the directed differentiation of pluripotent stem cells to beta-like cells, essential gaps still exist in generating stem cell-derived beta cells that are fully functional in vitro. This short review provides details of recent multi-'omics' studies of the human fetal pancreas, which are revealing granular information on the various cell types in the developing pancreas. It is anticipated that this fine mapping of the pancreatic cells at single-cell resolution will provide additional insights that can be utilised to reproducibly produce human beta cells in vitro that have the functional characteristics of beta cells within native human islets.

Genetic and cytometric analyses of subcutaneous adipose tissue in patients with hemophilia and HIV-associated lipodystrophy.

BACKGROUND: The authors recently performed plastic surgeries for a small number of patients with hemophilia, HIV infection, and morphologic evidence of lipodystrophy. Because the pathophysiological mechanism of HIV-associated lipodystrophy remains to be elucidated, we analyzed subcutaneous adipose tissues from the patients. METHODS: All six patients had previously been treated with older nucleoside analogue reverse-transcriptase inhibitors (NRTIs; stavudine, didanosine or zidovudine). Abdominal and inguinal subcutaneous fat samples were obtained from the HIV+ patients with hemophilia and HIV- healthy volunteers (n = 6 per group), and analyzed via DNA microarray, real-time PCR, flow cytometry and immunohistochemistry. RESULTS: The time from initial NRTI treatment to collecting samples were 21.7 years in average. Cytometric analysis revealed infiltration of inflammatory M1 macrophages into HIV-infected adipose tissue and depletion of adipose-derived stem cells, possibly due to exhaustion following sustained adipocyte death. Genetic analysis revealed that adipose tissue from HIV+ group had increased immune activation, mitochondrial toxicity, chronic inflammation, progressive fibrosis and adipocyte dysfunction (e.g. insulin resistance, inhibited adipocyte differentiation and accelerated apoptosis). Of note, both triglyceride synthesis and lipolysis were inhibited in adipose tissue from patients with HIV. CONCLUSIONS: Our findings provide important insights into the pathogenesis of HIV-associated lipodystrophy, suggesting that fat redistribution may critically depend on adipocytes' sensitivity to drug-induced mitochondrial toxicity, which may lead either to atrophy or metabolic complications.

Comparative study of bacterial flora in bronchoalveolar lavage fluid of pneumonia patients based on their pneumonia subtypes and comorbidities using 16S ribosomal RNA gene analysis.

INTRODUCTION: The culture method is the gold standard for identifying pathogenic bacteria in patients with pneumonia but often does not reflect the exact bacterial flora in pulmonary lesions of pneumonia, partly owing to easiness or difficulties in culturing certain bacterial species. We aimed to evaluate bacterial flora in bronchoalveolar lavage fluid (BALF) samples directly obtained from pneumonia lesions using 16S ribosomal RNA (rRNA) gene analysis to compare the results of the BALF culture method in each category of pneumonia. METHODS: Bacterial florae were detected by a combination of the culture method, and the clone library method using the 16S rRNA gene sequencing in BALF directly obtained from pneumonia lesions in pneumonia patients from April 2010 to March 2020 at the University of Occupational and Environmental Health, Japan, and affiliated hospitals. Clinical information of these patients was also collected, and lung microbiome was evaluated for each pneumonia category. RESULTS: Among 294 pneumonia patients (120 with community-acquired pneumonia (CAP), 101 with healthcare-associated pneumonia (HCAP), and 73 with hospital-acquired pneumonia (HAP)), significantly higher percentages of obligate anaerobes were detected in CAP than in HCAP and HAP patients by the clone library method. Corynebacterium species were significantly highly detected in HAP patients and patients with cerebrovascular diseases than in patients without, and Streptococcus pneumoniae was frequently detected in patients with diabetes mellitus. CONCLUSION: Obligate anaerobes may be underestimated in patients with CAP. Corynebacterium species should be regarded as the causative bacteria for pneumonia in patients with HAP and cerebrovascular diseases.

Study of The specificity of gut microbiota in adult patients with delayed-onset of atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is a common and recurrent skin disease. The first onset of AD in adults is known as adult-onset atopic dermatitis (AOAD). Gut microbiota is closely associated with AD, and the "gut-skin" axis is considered as a novel target for prevention of AD. However, only a few studies have analyzed AOAD, particularly the studies that compared differences in intestinal flora between AOAD and persistent AD patients. OBJECTIVE: To investigate main specificities of intestinal microbiota in AOAD patients, particularly comparing with persistent AD patients. METHODS: A comprehensive taxonomic and functional analysis of gut microbiota in 10 healthy, 12 AOAD, and 10 persistent AD patients was done by using bacterial 16S ribosomal RNA (rRNA) gene analysis. Chao1 and Shannon diversity indices were measured to analyze alpha diversity, and the linear discriminant analysis (LDA) effect size (LEfSe) algorithm was applied to identify differences in genus. RESULTS: The alpha diversity of gut microbiota in AOAD patients was decreased, with Escherichia-shigella (15.8%) being the predominant genus of AOAD group. Agathobacter and Dorea in AOAD patients were significantly reduced, whereas the relative level of Bacteroides pectinophilus group was remarkably elevated compared with healthy volunteers and persistent AD patients. CONCLUSION: The present study revealed differences in intestinal flora between AOAD, healthy adults, and non-adult onset of AD, and explored differential dominant bacteria between AOAD and persistent AD patients.

Endoscopic ultrasound-guided tissue acquisition for pancreatic ductal adenocarcinoma in the era of precision medicine.

Endoscopic ultrasound-guided tissue acquisition (EUS-TA) currently plays a central role in the diagnosis of pancreatic ductal adenocarcinoma (PDAC). Although fine-needle aspiration has been the gold standard, novel biopsy needles for fine-needle biopsy (FNB) were developed to overcome its limitations, which include low tumor cellularity and the inability to retain cellular architecture. Following recent improvements in FNB needles, the pathological diagnosis has shifted from cytology to histology and now to genetic diagnosis. Genetic analysis using EUS-TA samples began with a search for the presence of K-ras mutations. However, the introduction of next-generation sequencers has dramatically changed genetic analysis and led to the gradual elucidation of the mechanism of PDAC, enabling personalized medicine by performing multiple gene analyses simultaneously. Comprehensive genomic profiling is currently applied in the clinical setting and there is an increasing need for gene analysis using EUS-TA samples. Although target genome sequencing is feasible even with cytological specimens, it can be difficult to proceed with full genetic analysis including whole-exome sequence or whole-genome sequence if the samples are too small. Genetic analysis will become highly important in determining indications for personalized medicine such as poly (ADP-ribose) polymerase inhibitors or immune checkpoint inhibitors. Therefore, the endosonographer must always take gene analysis into consideration when collecting samples for diagnosis and further improvement of the puncture technique and needle development are anticipated in the future.

Gene Expression Landscape of Chronic Myeloid Leukemia K562 Cells Overexpressing the Tumor Suppressor Gene PTPRG.

This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose level of expression is altered by PTPRG modulation and Imatinib concentration. Statistical tests as differential expression analysis (DEA) supported by gene set enrichment analysis (GSEA) and modern methods of ontological term analysis are presented along with some results of current interest for forthcoming experimental research in the field of the transcriptomic landscape of CML. In particular, we present two methods that differ in the order of the analysis steps. After a gene selection based on fold-change value thresholding, we applied statistical tests to select differentially expressed genes. Therefore, we applied two different methods on the set of differentially expressed genes. With the first method (Method 1), we implemented GSEA, followed by the identification of transcription factors. With the second method (Method 2), we first selected the transcription factors from the set of differentially expressed genes and implemented GSEA on this set. Method 1 is a standard method commonly used in this type of analysis, while Method 2 is unconventional and is motivated by the intention to identify transcription factors more specifically involved in biological processes relevant to the CML condition. Both methods have been equipped in ontological knowledge mining and word cloud analysis, as elements of novelty in our analytical procedure. Data analysis identified RARG and CD36 as a potential PTPRG up-regulated genes, suggesting a possible induction of cell differentiation toward an erithromyeloid phenotype. The prediction was confirmed at the mRNA and protein level, further validating the approach and identifying a new molecular mechanism of tumor suppression governed by PTPRG in a CML context.