PLoS One. 2023 May 4;18(5):e0284173. doi: 10.1371/journal.pone.0284173. eCollection 2023.

ABSTRACT

The pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the biggest healthcare issue worldwide. This study aimed to develop a monoclonal antibody against SARS-CoV-2 from B cells of recovered COVID-19 patients, which might have beneficial therapeutic purposes for COVID-19 patients. We successfully generated human monoclonal antibodies (hmAbs) against the receptor binding domain (RBD) protein of SARS-CoV-2 using developed hybridoma technology. The isolated hmAbs against the RBD protein (wild-type) showed high binding activity and neutralized the interaction between the RBD and the cellular receptor angiotensin-converting enzyme 2 (ACE2) protein. Epitope binning and crystallography results displayed target epitopes of these antibodies in distinct regions beneficial in the mix as a cocktail. The 3D2 binds to conserved epitopes among multi-variants. Pseudovirion-based neutralization results revealed that the antibody cocktail, 1D1 and 3D2, showed high potency in multiple variants of SARS-CoV-2 infection. In vivo studies showed the ability of the antibody cocktail treatment (intraperitoneal (i.p.) administration) to reduce viral load (Beta variant) in blood and various tissues. While the antibody cocktail treatment (intranasal (i.n.) administration) could not significantly reduce the viral load in nasal turbinate and lung tissue, it could reduce the viral load in blood, kidney, and brain tissue. These findings revealed that the efficacy of the antibody cocktail, 1D1 and 3D2, should be further studied in animal models in terms of timing of administration, optimal dose, and efficacy to mitigate inflammation in targeted tissue such as nasal turbinate and lung.

PMID:37141227 | DOI:10.1371/journal.pone.0284173

Brief Bioinform. 2023 May 4:bbad178. doi: 10.1093/bib/bbad178. Online ahead of print.

ABSTRACT

Microbiome-based diagnosis of cancer is an increasingly important supplement for the genomics approach in cancer diagnosis, yet current models for microbiome-based diagnosis of cancer face difficulties in generality: not only diagnosis models could not be adapted from one cancer to another, but models built based on microbes from tissues could not be adapted for diagnosis based on microbes from blood. Therefore, a microbiome-based model suitable for a broad spectrum of cancer types is urgently needed. Here we have introduced DeepMicroCancer, a diagnosis model using artificial intelligence techniques for a broad spectrum of cancer types. Built based on the random forest models it has enabled superior performances on more than twenty types of cancers' tissue samples. And by using the transfer learning techniques, improved accuracies could be obtained, especially for cancer types with only a few samples, which could satisfy the requirement in clinical scenarios. Moreover, transfer learning techniques have enabled high diagnosis accuracy that could also be achieved for blood samples. These results indicated that certain sets of microbes could, if excavated using advanced artificial techniques, reveal the intricate differences among cancers and healthy individuals. Collectively, DeepMicroCancer has provided a new venue for accurate diagnosis of cancer based on tissue and blood materials, which could potentially be used in clinics.

PMID:37141141 | DOI:10.1093/bib/bbad178

Brief Bioinform. 2023 May 4:bbad168. doi: 10.1093/bib/bbad168. Online ahead of print.

ABSTRACT

With the rapid development of human intestinal microbiology and diverse microbiome-related studies and investigations, a large amount of data have been generated and accumulated. Meanwhile, different computational and bioinformatics models have been developed for pattern recognition and knowledge discovery using these data. Given the heterogeneity of these resources and models, we aimed to provide a landscape of the data resources, a comparison of the computational models and a summary of the translational informatics applied to microbiota data. We first review the existing databases, knowledge bases, knowledge graphs and standardizations of microbiome data. Then, the high-throughput sequencing techniques for the microbiome and the informatics tools for their analyses are compared. Finally, translational informatics for the microbiome, including biomarker discovery, personalized treatment and smart healthcare for complex diseases, are discussed.

PMID:37141135 | DOI:10.1093/bib/bbad168

Methods Mol Biol. 2023;2668:3-13. doi: 10.1007/978-1-0716-3203-1_1.

ABSTRACT

Extracellular vesicles (EVs) represent heterogeneous populations of membrane-bound vesicles shed from almost all kinds of cells. Although superior to conventional methods, most newly developed EV sensing platforms still require a certain number of EVs, measuring bulk signals from a group of vesicles. A new analytical approach that enables single EV analysis could be extremely valuable for understanding EVs' subtypes, heterogeneity, and production dynamics during disease development and progression. Here, we describe a new nanoplasmonic sensing platform for sensitive single EV analysis. Termed nPLEX-FL (nano-plasmonic EV analysis with enhanced fluorescence detection), the system amplifies EVs' fluorescence signals using periodic gold nanohole structures, enabling sensitive, multiplexed analysis of single EVs.

PMID:37140785 | DOI:10.1007/978-1-0716-3203-1_1

Virus Genes. 2023 May 4. doi: 10.1007/s11262-023-01995-z. Online ahead of print.

ABSTRACT

Although comprehensive vaccination is the cornerstone of public health programs to control hepatitis B virus (HBV) infections, 5% of people who receive the existing vaccine do not develop proper immunity against HBV. To overcome this challenge, researchers have tried using various protein fragments encoded by the virus genome to achieve better immunization rates. An important antigenic component of HBsAg called the preS2/S or M protein has also received much attention in this area. The gene sequences of preS2/S and Core18-27 peptide were extracted from the GenBank (NCBI). Final gene synthesis was conducted with pET28. Groups of BALB/c mice were immunized with 10 μg/ml of recombinant proteins and 1 μg/ml CPG7909 adjuvant. Serum levels of IF-γ, TNF-α, IL-2, IL-4, and IL-10 were measured by ELISA assay method on spleen cell cultures on day 45, and IgG1, IgG2a, and total IgG titers obtained from mice serum were quantified on days 14 and 45. Statistical analysis did not show any significant difference between the groups regarding IF-γ level. There were, however, significant differences in terms of IL-2 and IL-4 levels between the groups receiving preS2/S-C18-27 with and without adjuvant and the groups receiving both preS2/S and preS2/S-C18-27 (Plus Recomb-Plus Recomb: the group of mice that received both preS2/S and preS2/S-C18-27 simultaneously). The strongest total antibody production was induced by immunization with both recombinant proteins without CPG adjuvant. The groups that received both preS2/S and preS2/S-C18-27, whether with or without adjuvant, were significantly different from those that received the conventional vaccine considering most abundant interleukins. This difference suggested that higher levels of efficacy can be achieved by the use of multiple virus antigen fragments rather than using a single fragment.

PMID:37140777 | DOI:10.1007/s11262-023-01995-z

Elife. 2023 May 4;12:e87861. doi: 10.7554/eLife.87861.

ABSTRACT

Various aspects of olfactory memory are represented as modulated responses across different classes of neurons in C. elegans.

PMID:37140564 | DOI:10.7554/eLife.87861

OMICS. 2023 May 4. doi: 10.1089/omi.2023.0002. Online ahead of print.

ABSTRACT

COVID-19 caused by the SARS-CoV-2 infection is a systemic disease that affects multiple organs, biological pathways, and cell types. A systems biology approach would benefit the study of COVID-19 in the pandemic as well as the endemic state. Notably, patients with COVID-19 have dysbiosis of lung microbiota whose functional relevance to the host is largely unknown. We carried out a systems biology investigation of the impact of lung microbiome-derived metabolites on host immune system during COVID-19. RNAseq was performed to identify the host-specific pro- and anti-inflammatory differentially expressed genes (DEGs) in bronchial epithelium and alveolar cells during SARS-CoV-2 infection. The overlapping DEGs were harnessed to construct an immune network while their key transcriptional regulator was deciphered. We identified 68 overlapping genes from both cell types to construct the immune network, and Signal Transducer and Activator of Transcription 3 (STAT3) was found to regulate the majority of the network proteins. Furthermore, thymidine diphosphate produced from the lung microbiome had the highest affinity with STAT3 (-6.349 kcal/mol) than the known STAT3 inhibitors (n = 410), with an affinity ranging from -5.39 to 1.31 kcal/mol. In addition, the molecular dynamic studies showed distinguishable changes in the behavior of the STAT3 complex when compared with free STAT3. Overall, our results provide new observations on the importance of lung microbiome metabolites that regulate the host immune system in patients with COVID-19, and may open up new avenues for preventive medicine and therapeutics innovation.

PMID:37140561 | DOI:10.1089/omi.2023.0002

Elife. 2023 May 4;12:e74434. doi: 10.7554/eLife.74434.

ABSTRACT

A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation.

PMID:37140557 | DOI:10.7554/eLife.74434

Microbiol Spectr. 2023 May 4:e0462622. doi: 10.1128/spectrum.04626-22. Online ahead of print.

ABSTRACT

Armillaria ostoyae, a species among the destructive forest pathogens from the genus Armillaria, causes root rot disease on woody plants worldwide. Efficient control measures to limit the growth and impact of this severe underground pathogen are under investigation. In a previous study, a new soilborne fungal isolate, Trichoderma atroviride SZMC 24276 (TA), exhibited high antagonistic efficacy, which suggested that it could be utilized as a biocontrol agent. The dual culture assay results indicated that the haploid A. ostoyae-derivative SZMC 23085 (AO) (C18/9) is highly susceptible to the mycelial invasion of TA. In the present study, we analyzed the transcriptome of AO and that of TA in in vitro dual culture assays to test the molecular arsenal of Trichoderma antagonism and the defense mechanisms of Armillaria. We conducted time-course analysis and functional annotation and analyzed enriched pathways and differentially expressed genes including biocontrol-related candidate genes from TA and defense-related candidate genes from AO. The results indicated that TA deployed several biocontrol mechanisms when confronted with AO. In response, AO initiated multiple defense mechanisms to protect against the fungal attack. To our knowledge, the present study offers the first transcriptome analysis of a biocontrol fungus attacking AO. Overall, this study provides insights that aid the further exploration of plant pathogen-biocontrol agent interaction mechanisms. IMPORTANCE Armillaria species can survive for decades in the soil on dead woody debris, develop rapidly under favorable conditions, and harmfully infect newly planted forests. Our previous study found Trichoderma atroviride to be highly effective in controlling Armillaria growth; therefore, our current work explored the molecular mechanisms that might play a key role in Trichoderma-Armillaria interactions. Direct confrontation assays combined with time course-based dual transcriptome analysis provided a reliable system for uncovering the interactive molecular dynamics between the fungal plant pathogen and its mycoparasitic partner. Furthermore, using a haploid Armillaria isolate allowed us to survey the deadly prey-invading activities of the mycoparasite and the ultimate defensive strategies of its prey. Our current study provides detailed insights into the essential genes and mechanisms involved in Armillaria defense against Trichoderma and the genes potentially involved in the efficiency of Trichoderma to control Armillaria. In addition, using a sensitive haploid Armillaria strain (C18/9), with its complete genome data already available, also offers the opportunity to test possible variable molecular responses of Armillaria ostoyae toward diverse Trichoderma isolates with various biocontrol abilities. Initial molecular tests of the dual interactions may soon help to develop a targeted biocontrol intervention with mycoparasites against plant pathogens.

PMID:37140425 | DOI:10.1128/spectrum.04626-22

Gut Microbes. 2023 Jan-Dec;15(1):2205386. doi: 10.1080/19490976.2023.2205386.

ABSTRACT

Cross-cohort validation is essential for gut-microbiome-based disease stratification but was only performed for limited diseases. Here, we systematically evaluated the cross-cohort performance of gut microbiome-based machine-learning classifiers for 20 diseases. Using single-cohort classifiers, we obtained high predictive accuracies in intra-cohort validation (~0.77 AUC), but low accuracies in cross-cohort validation, except the intestinal diseases (~0.73 AUC). We then built combined-cohort classifiers trained on samples combined from multiple cohorts to improve the validation of non-intestinal diseases, and estimated the required sample size to achieve validation accuracies of >0.7. In addition, we observed higher validation performance for classifiers using metagenomic data than 16S amplicon data in intestinal diseases. We further quantified the cross-cohort marker consistency using a Marker Similarity Index and observed similar trends. Together, our results supported the gut microbiome as an independent diagnostic tool for intestinal diseases and revealed strategies to improve cross-cohort performance based on identified determinants of consistent cross-cohort gut microbiome alterations.

PMID:37140125 | DOI:10.1080/19490976.2023.2205386

Nucleic Acids Res. 2023 May 4:gkad353. doi: 10.1093/nar/gkad353. Online ahead of print.

ABSTRACT

Fundamental to post-transcriptional regulation, the in vivo binding of RNA binding proteins (RBPs) on their RNA targets heavily depends on RNA structures. To date, most methods for RBP-RNA interaction prediction are based on RNA structures predicted from sequences, which do not consider the various intracellular environments and thus cannot predict cell type-specific RBP-RNA interactions. Here, we present a web server PrismNet that uses a deep learning tool to integrate in vivo RNA secondary structures measured by icSHAPE experiments with RBP binding site information from UV cross-linking and immunoprecipitation in the same cell lines to predict cell type-specific RBP-RNA interactions. Taking an RBP and an RNA region with sequential and structural information as input ('Sequence & Structure' mode), PrismNet outputs the binding probability of the RBP and this RNA region, together with a saliency map and a sequence-structure integrative motif. The web server is freely available at http://prismnetweb.zhanglab.net.

PMID:37140045 | DOI:10.1093/nar/gkad353

J Natl Cancer Inst Monogr. 2023 May 4;2023(61):149-157. doi: 10.1093/jncimonographs/lgad005.

ABSTRACT

The overall goal of the annual Transdisciplinary Research in Energetics and Cancer (TREC) Training Workshop is to provide transdisciplinary training for scientists in energetics and cancer and clinical care. The 2022 Workshop included 27 early-to-mid career investigators (trainees) pursuing diverse TREC research areas in basic, clinical, and population sciences. The 2022 trainees participated in a gallery walk, an interactive qualitative program evaluation method, to summarize key takeaways related to program objectives. Writing groups were formed and collaborated on this summary of the 5 key takeaways from the TREC Workshop. The 2022 TREC Workshop provided a targeted and unique networking opportunity that facilitated meaningful collaborative work addressing research and clinical needs in energetics and cancer. This report summarizes the 2022 TREC Workshop's key takeaways and future directions for innovative transdisciplinary energetics and cancer research.

PMID:37139978 | DOI:10.1093/jncimonographs/lgad005

J Natl Cancer Inst Monogr. 2023 May 4;2023(61):84-103. doi: 10.1093/jncimonographs/lgad008.

ABSTRACT

Intermittent fasting entails restricting food intake during specific times of day, days of the week, religious practice, or surrounding clinically important events. Herein, the metabolic and circadian rhythm mechanisms underlying the proposed benefits of intermittent fasting for the cancer population are described. We summarize epidemiological, preclinical, and clinical studies in cancer published between January 2020 and August 2022 and propose avenues for future research. An outstanding concern regarding the use of intermittent fasting among cancer patients is that fasting often results in caloric restriction, which can put patients already prone to malnutrition, cachexia, or sarcopenia at risk. Although clinical trials do not yet provide sufficient data to support the general use of intermittent fasting in clinical practice, this summary may be useful for patients, caregivers, and clinicians who are exploring intermittent fasting as part of their cancer journey for clinical outcomes and symptom management.

PMID:37139971 | DOI:10.1093/jncimonographs/lgad008

Plant Physiol. 2023 May 4:kiad261. doi: 10.1093/plphys/kiad261. Online ahead of print.

ABSTRACT

Arabidopsis (Arabidopsis thaliana) T-DNA insertion collections are popular resources for fundamental plant research. Cinnamoyl-CoA reductase 1 (CCR1) catalyzes an essential step in the biosynthesis of the cell wall polymer lignin. Accordingly, the intronic transfer (T)-DNA insertion mutant ccr1-6 has reduced lignin levels and shows a stunted growth phenotype. Here, we report restoration of the ccr1-6 mutant phenotype and CCR1 expression levels after a genetic cross with a UDP-glucosyltransferase 72e1 (ugt72e1), -e2, -e3 T-DNA mutant. We discovered that the phenotypic recovery was not dependent on the UGT72E family loss of function but due to an epigenetic phenomenon called trans T-DNA suppression. Via trans T-DNA suppression, the gene function of an intronic T-DNA mutant was restored after the introduction of an additional T-DNA sharing identical sequences, leading to heterochromatinization and splicing out of the T-DNA-containing intron. Consequently, the suppressed ccr1-6 allele was named epiccr1-6. Long-read sequencing revealed that epiccr1-6, not ccr1-6, carries dense cytosine methylation over the full length of the T-DNA. We showed that the SAIL T-DNA in the UGT72E3 locus could trigger the trans T-DNA suppression of the GABI-Kat T-DNA in the CCR1 locus. Furthermore, we scanned the literature for other potential cases of trans T-DNA suppression in Arabidopsis and found that 22% of the publications matching our query report on double or higher-order T-DNA mutants that meet the minimal requirements for trans T-DNA suppression. These combined observations indicate that intronic T-DNA mutants need to be used with caution since methylation of intronic T-DNA might derepress gene expression and can thereby confound results.

PMID:37139862 | DOI:10.1093/plphys/kiad261

JACC Basic Transl Sci. 2023 Feb 1;8(4):406-418. doi: 10.1016/j.jacbts.2022.10.010. eCollection 2023 Apr.

ABSTRACT

Dilated cardiomyopathy is a heterogeneous disease characterized by multiple genetic and environmental etiologies. The majority of patients are treated the same despite these differences. The cardiac transcriptome provides information on the patient's pathophysiology, which allows targeted therapy. Using clustering techniques on data from the genotype, phenotype, and cardiac transcriptome of patients with early- and end-stage dilated cardiomyopathy, more homogeneous patient subgroups are identified based on shared underlying pathophysiology. Distinct patient subgroups are identified based on differences in protein quality control, cardiac metabolism, cardiomyocyte function, and inflammatory pathways. The identified pathways have the potential to guide future treatment and individualize patient care.

PMID:37138803 | PMC:PMC10149655 | DOI:10.1016/j.jacbts.2022.10.010

iScience. 2023 Apr 10;26(5):106635. doi: 10.1016/j.isci.2023.106635. eCollection 2023 May 19.

ABSTRACT

Enhanced phenotypic diversity increases a population's likelihood of surviving catastrophic conditions. Hsp90, an essential molecular chaperone and a central network hub in eukaryotes, has been observed to suppress or enhance the effects of genetic variation on phenotypic diversity in response to environmental cues. Because many Hsp90-interacting genes are involved in signaling transduction pathways and transcriptional regulation, we tested how common Hsp90-dependent differential gene expression is in natural populations. Many genes exhibited Hsp90-dependent strain-specific differential expression in five diverse yeast strains. We further identified transcription factors (TFs) potentially contributing to variable expression. We found that on Hsp90 inhibition or environmental stress, activities or abundances of Hsp90-dependent TFs varied among strains, resulting in differential strain-specific expression of their target genes, which consequently led to phenotypic diversity. We provide evidence that individual strains can readily display specific Hsp90-dependent gene expression, suggesting that the evolutionary impacts of Hsp90 are widespread in nature.

PMID:37138775 | PMC:PMC10149407 | DOI:10.1016/j.isci.2023.106635

Front Microbiol. 2023 Apr 17;14:1164553. doi: 10.3389/fmicb.2023.1164553. eCollection 2023.

ABSTRACT

INTRODUCTION: Microbial communities inhabiting the human infant gut are important for immune system development and lifelong health. One critical exposure affecting the bacterial colonization of the infant gut is consumption of human milk, which contains diverse microbial communities and prebiotics. We hypothesized that human milk-associated microbial profiles are associated with those of the infant gut.

METHODS: Maternal-infant dyads enrolled in the New Hampshire Birth Cohort Study (n = 189 dyads) contributed breast milk and infant stool samples collected approximately at 6 weeks, 4 months, 6 months, 9 months, and 12 months postpartum (n = 572 samples). Microbial DNA was extracted from milk and stool and the V4-V5 region of the bacterial 16S rRNA gene was sequenced.

RESULTS: Clustering analysis identified three breast milk microbiome types (BMTs), characterized by differences in Streptococcus, Staphylococcus, Pseudomonas, Acinetobacter, and microbial diversity. Four 6-week infant gut microbiome types (6wIGMTs) were identified, differing in abundances of Bifidobacterium, Bacteroides, Clostridium, Streptococcus, and Escherichia/Shigella, while two 12-month IGMTs (12mIGMTs) differed primarily by Bacteroides presence. At 6 weeks, BMT was associated with 6wIGMT (Fisher's exact test value of p = 0.039); this association was strongest among infants delivered by Cesarean section (Fisher's exact test value of p = 0.0028). The strongest correlations between overall breast milk and infant stool microbial community structures were observed when comparing breast milk samples to infant stool samples collected at a subsequent time point, e.g., the 6-week breast milk microbiome associated with the 6-month infant gut microbiome (Mantel test Z-statistic = 0.53, value of p = 0.001). Streptoccous and Veillonella species abundance were correlated in 6-week milk and infant stool, and 4- and 6-month milk Pantoea species were associated with infant stool Lachnospiraceae genera at 9 and 12 months.

DISCUSSION: We identified clusters of human milk and infant stool microbial communities that were associated in maternal-infant dyads at 6 weeks of life and found that milk microbial communities were more strongly associated with infant gut microbial communities in infants delivered operatively and after a lag period. These results suggest that milk microbial communities have a long-term effect on the infant gut microbiome both through sharing of microbes and other molecular mechanisms.

PMID:37138613 | PMC:PMC10149717 | DOI:10.3389/fmicb.2023.1164553

Bioinformatics. 2023 May 3:btad210. doi: 10.1093/bioinformatics/btad210. Online ahead of print.

ABSTRACT

MOTIVATION: There is a need for easily accessible implementations that measure the strength of both linear and non-linear relationships between metabolites in biological systems as an approach for data-driven network development. While multiple tools implement linear Pearson and Spearman methods, there are no such tools that assess distance correlation.

RESULTS: We present here SIgned Distance COrrelation (SiDCo). SiDCo is a GUI-platform for calculation of distance correlation in omics data, measuring linear and non-linear dependences between variables, as well as correlation between vectors of different lengths, e.g., different sample sizes. By combining the sign of the overall trend from Pearson's correlation with distance correlation values, we further provide a novel signed distance correlation of particular use in metabolomic and lipidomic analyses. Distance correlations can be selected as one-to-one or one-to-all correlations, showing relationships between each feature and all other features one at a time or in combination. Additionally, we implement partial distance correlation, calculated using the Gaussian Graphical model approach adapted to distance covariance. Our platform provides an easy-to-use software implementation that can be applied to the investigation of any dataset.

AVAILABILITY: The SiDCo software application is freely available at https://complimet.ca/sidco.

SUPPLEMENTARY INFORMATION: Supplementary help pages are provided at https://complimet.ca/sidco. Supplementary Material shows an example of an application of SiDCo in metabolomics.

PMID:37137236 | DOI:10.1093/bioinformatics/btad210

J Neuroinflammation. 2023 May 3;20(1):106. doi: 10.1186/s12974-023-02785-y.

ABSTRACT

TNF signaling is an essential regulator of cellular homeostasis. Through its two receptors TNFR1 and TNFR2, soluble versus membrane-bound TNF enable cell death or survival in a variety of cell types. TNF-TNFRs signaling orchestrates important biological functions such as inflammation, neuronal activity as well as tissue de- and regeneration. TNF-TNFRs signaling is a therapeutic target for neurodegenerative diseases such as multiple sclerosis (MS) and Alzheimer's disease (AD), but animal and clinical studies yielded conflicting findings. Here, we ask whether a sequential modulation of TNFR1 and TNFR2 signaling is beneficial in experimental autoimmune encephalomyelitis (EAE), an experimental mouse model that recapitulates inflammatory and demyelinating aspects of MS. To this end, human TNFR1 antagonist and TNFR2 agonist were administered peripherally at different stages of disease development in TNFR-humanized mice. We found that stimulating TNFR2 before onset of symptoms leads to improved response to anti-TNFR1 therapeutic treatment. This sequential treatment was more effective in decreasing paralysis symptoms and demyelination, when compared to single treatments. Interestingly, the frequency of the different immune cell subsets is unaffected by TNFR modulation. Nevertheless, treatment with only a TNFR1 antagonist increases T-cell infiltration in the central nervous system (CNS) and B-cell cuffing at the perivascular sites, whereas a TNFR2 agonist promotes Treg CNS accumulation. Our findings highlight the complicated nature of TNF signaling which requires a timely balance of selective activation and inhibition of TNFRs in order to exert therapeutic effects in the context of CNS autoimmunity.

PMID:37138340 | DOI:10.1186/s12974-023-02785-y

BMC Genomics. 2023 May 3;24(1):230. doi: 10.1186/s12864-023-09298-1.

ABSTRACT

BACKGROUND: The reduction in phenotypic performance of a population due to mating between close relatives is called inbreeding depression. The genetic background of inbreeding depression for semen traits is poorly understood. Thus, the objectives were to estimate the effect of inbreeding and to identify genomic regions underlying inbreeding depression of semen traits including ejaculate volume (EV), sperm concentration (SC), and sperm motility (SM). The dataset comprised ~ 330 K semen records from ~ 1.5 K Holstein bulls genotyped with 50 K single nucleotide polymorphism (SNP) BeadChip. Genomic inbreeding coefficients were estimated using runs of homozygosity (i.e., FROH > 1 Mb) and excess of SNP homozygosity (FSNP). The effect of inbreeding was estimated by regressing phenotypes of semen traits on inbreeding coefficients. Associated variants with inbreeding depression were also detected by regressing phenotypes on ROH state of the variants.

RESULTS: Significant inbreeding depression was observed for SC and SM (p < 0.01). A 1% increase in FROH reduced SM and SC by 0.28% and 0.42% of the population mean, respectively. By splitting FROH into different lengths, we found significant reduction in SC and SM due to longer ROH, which is indicative of more recent inbreeding. A genome-wide association study revealed two signals positioned on BTA 8 associated with inbreeding depression of SC (p < 0.00001; FDR < 0.02). Three candidate genes of GALNTL6, HMGB2, and ADAM29, located in these regions, have established and conserved connections with reproduction and/or male fertility. Moreover, six genomic regions on BTA 3, 9, 21 and 28 were associated with SM (p < 0.0001; FDR < 0.08). These genomic regions contained genes including PRMT6, SCAPER, EDC3, and LIN28B with established connections to spermatogenesis or fertility.

CONCLUSIONS: Inbreeding depression adversely affects SC and SM, with evidence that longer ROH, or more recent inbreeding, being especially detrimental. There are genomic regions associated with semen traits that seems to be especially sensitive to homozygosity, and evidence to support some from other studies. Breeding companies may wish to consider avoiding homozygosity in these regions for potential artificial insemination sires.

PMID:37138201 | DOI:10.1186/s12864-023-09298-1