Genetic Background Research Articles

Generation of an induced pluripotent stem cell line (BIORTCi001-A) from a healthy adult indigenous Nigerian participant

Genetic backgrounds influence cellular phenotypes, drug responses, and health outcomes, yet most human iPSC lines are derived from individuals of European descent, with lines from indigenous Africans particularly scarce. Addressing this gap, we generated iPSCs from dermal fibroblasts of a healthy 60-year-old indigenous Nigerian male of the Babur ethnic group using Sendai virus. The iPSC line displayed a normal karyotype, was characterized for pluripotency markers and differentiated into neural progenitor cells and astrocytes. To enhance African representation in research, this iPSC line will be available to the scientific community, with ongoing efforts focused on creating an open-access African iPSC biobank.Resource Table:

Innovating Thiopurine Therapeutic Drug Monitoring: A Systematic Review and Meta-Analysis on DNA-Thioguanine Nucleotides (DNA-TG) as an Inclusive Biomarker in Thiopurine Therapy.

Thioguanine (TG), azathioprine (AZA), and mercaptopurine (MP) are thiopurine prodrugs commonly used to treat diseases, such as leukemia and inflammatory bowel disease (IBD). 6-thioguanine nucleotides (6-TGNs) have been commonly used for monitoring treatment. High levels of 6-TGNs in red blood cells (RBCs) have been associated with leukopenia, the cutoff levels that predict this side effect remain uncertain. Thiopurines are metabolized and incorporated into leukocyte DNA. Measuring levels of DNA-incorporated thioguanine (DNA-TG) may be a more suitable method for predicting clinical response and toxicities such as leukopenia. Unfortunately, most methodologies to assay 6-TGNs are unable to identify the impact of NUDT15 variants, effecting mostly ethnic populations (e.g., Chinese, Indian, Malay, Japanese, and Hispanics). DNA-TG tackles this problem by directly measuring thioguanine in the DNA, which can be influenced by both TPMT and NUDT15 variants. While RBC 6-TGN concentrations have traditionally been used to optimize thiopurine therapy due to their ease and affordability of measurement, recent developments in liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have made measuring DNA-TG concentrations in lymphocytes accurate, reproducible, and affordable. The objective of this systematic review was to assess the current evidence of DNA-TG levels as marker for thiopurine therapy, especially with regards to NUDT15 variants. A systematic review and meta-analysis were performed on the current evidence for DNA-TG as a marker for monitoring thiopurine therapy, including methods for measurement and the illustrative relationship between DNA-TG and various gene variants (such as TPMT, NUDT15, ITPA, NT5C2, and MRP4). PubMed and Embase were systematically searched up to April 2024 for published studies, using the keyword "DNA-TG" with MeSH terms and synonyms. The electronic search strategy was augmented by a manual examination of references cited in articles, recent reviews, editorials, and meta-analyses. A meta-analysis was performed using R studio 4.1.3. to investigate the difference between the coefficients (Fisher's z-transformed correlation coefficient) of DNA-TG and 6-TGNs levels. A meta-analysis was performed using RevMan version 5.4 to investigate the difference in DNA-TG levels between patients with or without leukopenia using randomized effect size model. The risk of bias was assessed using the Newcastle-Ottowa quality assessment scale. In this systematic review, 21 studies were included that measured DNA-TG levels in white blood cells for either patients with ALL (n = 16) or IBD (n = 5). In our meta-analysis, the overall mean difference between patients with leukopenia (ALL + IBD) versus no leukopenia was 134.15 fmol TG/µg DNA [95% confidence interval (CI) (83.78-184.35), P < 0.00001; heterogeneity chi squared of 5.62, I2 of 47%]. There was a significant difference in DNA-TG levels for patients with IBD with and without leukopenia [161.76 fmol TG/µg DNA; 95% CI (126.23-197.29), P < 0.00001; heterogeneity chi squared of 0.20, I2 of 0%]. No significant difference was found in DNA-TG level between patients with ALL with or without leukopenia (57.71 fmol TG/µg DNA [95% CI (-22.93 to 138.35), P < 0.80]). DNA-TG monitoring was found to be a promising method for predicting relapse rates in patients with ALL, and DNA-TG levels are likely a better predictor for leukopenia in patients with IBD than RBC 6-TGNs levels. DNA-TG levels have been shown to correlate with various gene variants (TPMT, NUDT15, ITPA, and MRP4) in various studies, points to its potential as a more informative marker for guiding thiopurine therapy across diverse genetic backgrounds. This systematic review strongly supports the further investigation of DNA-TG as a marker for monitoring thiopurine therapy. Its correlation with treatment outcomes, such as relapse-free survival in ALL and the risk of leukopenia in IBD, underscores its role in enhancing personalized treatment approaches. DNA-TG effectively identifies NUDT15 variants and predicts late leukopenia in patients with IBD, regardless of their NUDT15 variant status. The recommended threshold for late leukopenia prediction in patients with IBD with DNA-TG is suggested to be between 320 and 340 fmol/µg DNA. More clinical research on DNA-TG implementation is mandatory to improve patient care and to improve inclusivity in thiopurine treatment.

CRISPRi-TnSeq maps genome-wide interactions between essential and non-essential genes in bacteria.

Genetic interactions identify functional connections between genes and pathways, establishing gene functions or druggable targets. Here we use CRISPRi-TnSeq, CRISPRi-mediated knockdown of essential genes alongside TnSeq-mediated knockout of non-essential genes, to map genome-wide interactions between essential and non-essential genes in Streptococcus pneumoniae. Transposon-mutant libraries constructed in 13 CRISPRi strains enabled screening of ~24,000 gene pairs. This identified 1,334 genetic interactions, including 754 negative and 580 positive interactions. Network analyses show that 17 non-essential genes pleiotropically interact with more than half the essential genes tested. Validation experiments confirmed that a 7-gene subset protects against perturbations. Furthermore, we reveal hidden redundancies that compensate for essential gene loss, relationships between cell wall synthesis, integrity and cell division, and show that CRISPRi-TnSeq identifies synthetic and suppressor-type relationships between both functionally linked and disparate genes and pathways. Importantly, in species where CRISPRi and Tn-Seq are established, CRISPRi-TnSeq should be straightforward to implement.

Experimental evolution of gene essentiality in bacteria.

Essential gene products carry out fundamental cellular activities in interaction with other components. However, the lack of essential gene mutants and appropriate methodologies to link essential gene functions with their partners poses significant challenges. Here, we have generated deletion mutants in 32 genes previously identified as essential, with 23 mutants showing extremely slow growth in the SK36 strain of Streptococcus sanguinis . Whole-genome sequencing of 243 independently evolved populations of these mutants has identified >1000 spontaneous suppressor mutations in experimental evolution, many of which are new gene and pathway relationships, such as F1Fo-ATPase/V1V1-ATPase/TrkA1-H1 gene pathway. Patterns of spontaneous mutations occurring in essential gene mutants differed from those found in wildtype. While gene duplications occurred rarely, substitutions, deletions, and insertions were prevalent in evolved populations. These essential gene deletion mutants and spontaneous mutations fixed in the mutant populations during evolution established a foundation for understanding gene essentiality and the interaction of essential genes in networks.

Highly sensitive response to the toxicity of environmental chemicals in transparent casper zebrafish

The response sensitivity to toxic substances is the most concerned performance of animal model in chemical risk assessment. Casper (mitfaw2/w2;mpv17a9/a9), a transparent zebrafish mutant, is a useful in vivo model for toxicological assessment. However, the ability of casper to respond to the toxicity of exogenous chemicals is unknown. In this study, zebrafish embryos were exposed to five environmental chemicals, chlorpyrifos, lindane, α-endosulfan, bisphenol A, tetrabromobisphenol A (TBBPA), and an antiepileptic drug valproic acid. The half-lethal concentration (LC50) values of these chemicals in casper embryos were 62–87 % of that in the wild-type. After TBBPA exposure, the occurrence of developmental defects in the posterior blood island of casper embryos was increased by 67–77 % in relative to the wild-type, and the half-maximal effective concentration (EC50) in casper was 73 % of that in the wild-type. Moreover, the casper genetic background significantly increased the hyperlocomotion caused by chlorpyrifos and lindane exposure compared with the wild-type. These results demonstrated that casper had greater susceptibility to toxicity than wild-type zebrafish in acute toxicity, developmental toxicity and neurobehavioral toxicity assessments. Our data will inform future toxicological studies in casper and accelerate the development of efficient approaches and strategies for toxicity assessment via the use of casper.

ADR-2 regulates fertility and oocyte fate in C. elegans.

RNA binding proteins play essential roles in coordinating germline gene expression and development in all organisms. Here, we report that loss of ADR-2, a member of the Adenosine DeAminase acting on RNA (ADAR) family of RNA binding proteins and the sole adenosine-to-inosine RNA editing enzyme in C. elegans, can improve fertility in multiple genetic backgrounds. First, we show that loss of RNA editing by ADR-2 restores normal embryo production to subfertile animals that transgenically express a vitellogenin (yolk protein) fusion to green fluorescent protein. Using this phenotype, a high-throughput screen was designed to identify RNA binding proteins that when depleted yield synthetic phenotypes with loss of adr-2. The screen uncovered a genetic interaction between ADR-2 and SQD-1, a member of the heterogenous nuclear ribonucleoprotein (hnRNP) family of RNA binding proteins. Microscopy, reproductive assays, and high-throughput sequencing reveal that sqd-1 is essential for the onset of oogenesis and oogenic gene expression in young adult animals, and that loss of adr-2 can counteract the effects of loss of sqd-1 on gene expression and rescue the switch from spermatogenesis to oogenesis. Together, these data demonstrate that ADR-2 can contribute to the suppression of fertility and suggest novel roles for both RNA editing-dependent and independent mechanisms in regulating embryogenesis.

Coronavirus disease 2019-related myocarditis genes contribute to ECMO prognosis

BackgroundAcute myocardial injury, cytokine storms, hypoxemia and pathogen-mediated damage were the major causes responsible for mortality induced by coronavirus disease 2019 (COVID-19)-related myocarditis. These need ECMO treatment. We investigated differentially expressed genes (DEGs) in patients with COVID-19-related myocarditis and ECMO prognosis.MethodsGSE150392 and GSE93101 were analyzed to identify DEGs. A Venn diagram was used to obtain the same transcripts between myocarditis-related and ECMO-related DEGs. Enrichment pathway analysis was performed and hub genes were identified. Pivotal miRNAs, transcription factors, and chemicals with the screened gene interactions were identified. The GSE167028 dataset and single-cell sequencing data were used to validate the screened genes.ResultsUsing a Venn diagram, 229 overlapping DEGs were identified between myocarditis-related and ECMO-related DEGs, which were mainly involved in T cell activation, contractile actin filament bundle, actomyosin, cyclic nucleotide phosphodiesterase activity, and cytokine-cytokine receptor interaction. 15 hub genes and 15 neighboring DEGs were screened, which were mainly involved in the positive regulation of T cell activation, integrin complex, integrin binding, the PI3K-Akt signaling pathway, and the TNF signaling pathway. Data in GSE167028 and single-cell sequencing data were used to validate the screened genes, and this demonstrated that the screened genes CCL2, APOE, ITGB8, LAMC2, COL6A3 and TNC were mainly expressed in fibroblast cells; IL6, ITGA1, PTK2, ITGB5, IL15, LAMA4, CAV1, SNCA, BDNF, ACTA2, CD70, MYL9, DPP4, ENO2 and VEGFC were expressed in cardiomyocytes; IL6, PTK2, ITGB5, IL15, APOE, JUN, SNCA, CD83, DPP4 and ENO2 were expressed in macrophages; and IL6, ITGA1, PTK2, ITGB5, IL15, VCAM1, LAMA4, CAV1, ACTA2, MYL9, CD83, DPP4, ENO2, VEGFC and IL32 were expressed in vascular endothelial cells.ConclusionThe screened hub genes, IL6, ITGA1, PTK2, ITGB3, ITGB5, CCL2, IL15, VCAM1, GZMB, APOE, ITGB8, LAMA4, LAMC2, COL6A3 and TNFRSF9, were validated using GEO dataset and single-cell sequencing data, which may be therapeutic targets patients with myocarditis to prevent MI progression and adverse cardiovascular events.

Structural Assessment of Chlamydia trachomatis Major Outer Membrane Protein (MOMP)-Derived Vaccine Antigens and Immunological Profiling in Mice with Different Genetic Backgrounds.

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infections (STIs) worldwide. Ct infections are often asymptomatic in women, leading to severe reproductive tract sequelae. Development of a vaccine against Chlamydia is crucial. The Chlamydia major outer membrane protein (MOMP) is a prime vaccine antigen candidate, and it can elicit both neutralizing antibodies and protective CD4+ T cell responses. We have previously designed chimeric antigens composed of immunogenic variable regions (VDs) and conserved regions (CDs) of MOMP from Chlamydia muridarum (Cm) expressed into a carrier protein (PorB), and we have shown that these were protective in a mouse model of Cm respiratory infection. Here, we generated corresponding constructs based on MOMP from Ct serovar F. Preliminary structure analysis of the three antigens, PorB/VD1-3, PorB/VD1-4 and PorB/VD1-2-4, showed that they retained structure features consistent with those of PorB. The antigens induced robust humoral and cellular responses in mice with different genetic backgrounds. The antibodies were cross-reactive against Ct, but only anti-PorB/VD1-4 and anti-PorB/VD1-2-4 IgG antibodies were neutralizing, likely due to the antigen specificity. The cellular responses included proliferation in vitro and production of IFN-γ by splenocytes following Ct re-stimulation. Our results support further investigation of the PorB/VD antigens as potential protective candidates for a Chlamydia subunit vaccine.

Sst- and Vip-Cre mouse lines without age-related hearing loss.

GABAergic interneurons, including somatostatin (SST) and vasoactive intestinal peptide (VIP) positive cells, play a crucial role in cortical circuit processing. Cre recombinase-mediated manipulation of these interneurons is facilitated by commercially available knock-in mouse strains such as Sst-IRES-Cre (Sst-Cre) and Vip-IRES-Cre (Vip-Cre). However, these strains are troublesome for hearing research because they are only available on the C57BL/6 genetic background, which suffer from early onset age-related hearing loss (AHL) due to a mutation of the Cdh23 gene. To overcome this limitation, we backcrossed Sst-Cre and Vip-Cre mice to CBA mice to create normal-hearing offspring with the desired Cre transgenes. We confirmed that in these "CBA Cre" lines, Cre drives appropriate expression of Cre-dependent genes, by crossing CBA Cre mice to Ai14 reporter mice. To assess the hearing capabilities of the CBA Cre mice, we measured auditory brainstem responses (ABRs) using clicks and tones. CBA Cre mice showed significantly lower ABR thresholds compared to C57 control mice at 3, 6, 9, and 12 months. In conclusion, our study successfully generated Sst-Cre and Vip-Cre mouse lines on the CBA background that will be valuable tools for investigating the roles of SST and VIP positive interneurons without the confounding effects of age-related hearing loss.

Unraveling Tourette's Syndrome: Genetic and Environmental Interactions, Diagnosis Challenges, and Emerging Treatments

Unraveling Tourette's Syndrome: Genetic and Environmental Interactions, Diagnosis Challenges, and Emerging Treatments

Artificial Intelligence-Driven Prediction Revealed CFTR Associated with Therapy Outcome of Breast Cancer: A Feasibility Study.

In silico tools capable of predicting the functional consequences of genomic differences between individuals, many of which are AI-driven, have been the most effective over the past two decades for non-synonymous single nucleotide variants (nsSNVs). When appropriately selected for the purpose of the study, a high predictive performance can be expected. In this feasibility study, we investigate the distribution of nsSNVs with an allele frequency below 5%. To classify the putative functional consequence, a tier-based filtration led by AI-driven predictors and scoring system was implemented to the overall decision-making process, resulting in a list of prioritised genes. The study has been conducted on breast cancer patients of homogeneous ethnicity. Germline rare variants have been sequenced in genes that influence pharmacokinetic parameters of anticancer drugs or molecular signalling pathways in cancer. After AI-driven functional pathogenicity classification and data mining in pharmacogenomic (PGx) databases, variants were collapsed to the gene level and ranked according to their putative deleterious role. In breast cancer patients, seven of the twelve genes prioritised based on the predictions were found to be associated with response to oncotherapy, histological grade, and tumour subtype. Most importantly, we showed that the group of patients with at least one rare nsSNVs in cystic fibrosis transmembrane conductance regulator (CFTR) had significantly reduced disease-free (log rank, p = 0.002) and overall survival (log rank, p = 0.006). AI-driven in silico analysis with PGx data mining provided an effective approach navigating for functional consequences across germline genetic background, which can be easily integrated into the overall decision-making process for future studies. The study revealed a statistically significant association with numerous clinicopathological parameters, including treatment response. Our study indicates that CFTR may be involved in the processes influencing the effectiveness of oncotherapy or in the malignant progression of the disease itself.

Elimination of the extra chromosome of Dup15q syndrome iPSCs for cellular and molecular investigation

Chromosome 15q11.2–13.1 duplication (Dup15q) syndrome is one of the most common autism spectrum disorders (ASDs) associated with copy number variants (CNVs). For the analysis of CNV-relevant pathological cellular phenotypes, a CNV-corrected isogenic cell line is useful for excluding the influence of genetic background. Here, we devised a strategy to remove the isodicentric chromosome 15 by inserting a puro-ΔTK selection cassette into the extra chromosome using the CRISPR-Cas9 system, followed by a subsequent two-step drug selection. A series of assays, including qPCR-based copy number analysis and karyotype analysis, confirmed the elimination of the extra chromosome. Furthermore, cerebral organoids were generated from the parental Dup15q iPSCs and their isogenic iPSCs. scRNA-seq analysis revealed the alteration of expression levels in ion-channel-related genes and synapse-related genes in glutamatergic and GABAergic neurons in Dup15q organoids, respectively. The established isogenic cell line is a valuable resource for unraveling cellular and molecular alterations associated with Dup15q syndrome.

Integrative Bioinformatics Analysis for Targeting Hub Genes in Hepatocellular Carcinoma Treatment

Background: The damage in the liver and hepatocytes is where the primary liver cancer begins, and this is referred to as Hepatocellular Carcinoma (HCC). One of the best methods for detecting changes in gene expression of hepatocellular carcinoma is through bioinformatics approaches. Objective: This study aimed to identify potential drug target(s) hubs mediating HCC progression using computational approaches through gene expression and protein-protein interaction datasets. Methodology: Four datasets related to HCC were acquired from the GEO database, and Differentially Expressed Genes (DEGs) were identified. Using Evenn, the common genes were chosen. Using the Fun Rich tool, functional associations among the genes were identified. Further, protein-protein interaction networks were predicted using STRING, and hub genes were identified using Cytoscape. The selected hub genes were subjected to GEPIA and Shiny GO analysis for survival analysis and functional enrichment studies for the identified hub genes. The up-regulating genes were further studied for immunohistopathological studies using HPA to identify gene/protein expression in normal vs HCC conditions. Drug Bank and Drug Gene Interaction Database were employed to find the reported drug status and targets. Finally, STITCH was performed to identify the functional association between the drugs and the identified hub genes. Results: The GEO2R analysis for the considered datasets identified 735 upregulating and 284 downregulating DEGs. Functional gene associations were identified through the Fun Rich tool. Further, PPIN network analysis was performed using STRING. A comparative study was carried out between the experimental evidence and the other seven data evidence in STRING, revealing that most proteins in the network were involved in protein-protein interactions. Further, through Cytoscape plugins, the ranking of the genes was analyzed, and densely connected regions were identified, resulting in the selection of the top 20 hub genes involved in HCC pathogenesis. The identified hub genes were: KIF2C, CDK1, TPX2, CEP55, MELK, TTK, BUB1, NCAPG, ASPM, KIF11, CCNA2, HMMR, BUB1B, TOP2A, CENPF, KIF20A, NUSAP1, DLGAP5, PBK, and CCNB2. Further, GEPIA and Shiny GO analyses provided insights into survival ratios and functional enrichment studied for the hub genes. The HPA database studies further found that upregulating genes were involved in changes in protein expression in Normal vs HCC tissues. These findings indicated that hub genes were certainly involved in the progression of HCC. STITCH database studies uncovered that existing drug molecules, including sorafenib, regorafenib, cabozantinib, and lenvatinib, could be used as leads to identify novel drugs, and identified hub genes could also be considered as potential and promising drug targets as they are involved in the gene-chemical interaction networks. Conclusion: The present study involved various integrated bioinformatics approaches, analyzing gene expression and protein-protein interaction datasets, resulting in the identification of 20 topranked hubs involved in the progression of HCC. They are KIF2C, CDK1, TPX2, CEP55, MELK, TTK, BUB1, NCAPG, ASPM, KIF11, CCNA2, HMMR, BUB1B, TOP2A, CENPF, KIF20A, NUSAP1, DLGAP5, PBK, and CCNB2. Gene-chemical interaction network studies uncovered that existing drug molecules, including sorafenib, regorafenib, cabozantinib, and lenvatinib, can be used as leads to identify novel drugs, and the identified hub genes can be promising drug targets. The current study underscores the significance of targeting these hub genes and utilizing existing molecules to generate new molecules to combat liver cancer effectively and can be further explored in terms of drug discovery research to develop treatments for HCC.

GPS-Net: discovering prognostic pathway modules based on network regularized kernel learning.

The search for prognostic biomarkers capable of predicting patient outcomes, by analyzing gene expression in tissue samples and other molecular profiles, remains largely on single-gene-based or global-gene-search approaches. Gene-centric approaches, while foundational, fail to capture the higher-order dependencies that reflect the activities of co-regulated processes, pathway alterations, and regulatory networks, all of which are crucial in determining the patient outcomes in complex diseases like cancer. Here, we introduce GPS-Net, a computational framework that fills the gap in efficiently identifying prognostic modules by incorporating the holistic pathway structures and the network of gene interactions. By innovatively incorporating advanced multiple kernel learning techniques and network-based regularization, the proposed method not only enhances the accuracy of biomarker and pathway identification but also significantly reduces computational complexity, as demonstrated by extensive simulation studies. Applying GPS-Net, we identified key pathways that are predictive of patient outcomes in a cancer immunotherapy study. Overall, our approach provides a novel framework that renders genome-wide pathway-level prognostic analysis both feasible and scalable, synergizing both mechanism-driven and data-driven for precision genomics.

Genomic profiling of methicillin-sensitive Staphylococcus aureus (MSSA) isolates in Kuwait hospitals.

Staphylococcus aureus is an important pathogen that causes mild to invasive infections in hospitals and the community. Although methicillin-susceptible Staphylococcus aureus (MSSA) isolates continue to cause different infections, there is no data on the genetic backgrounds of the MSSA colonizing or causing infections in Kuwait hospitals. This study aimed to investigate MSSA isolated from patients admitted to Kuwait hospitals for antibiotic resistance and genetic backgrounds to understand their clonal composition. Consecutive MSSA isolates were collected from single patients during two surveillance periods in 2016 and 2021 in 13 public hospitals. The isolates were characterized using antibiogram, staphylococcal protein A (spa) typing, DNA microarray analysis, and multilocus sequence typing (MLST) using standard protocols. A total of 446 MSSA was cultured from different clinical samples in 2016 (n = 240) and 2021 (n = 206). All isolates were susceptible to vancomycin [minimum inhibitory concentration (MIC) ≤ 2 mg/L], teicoplanin (MIC ≤2 mg/L), linezolid (MIC ≤4 mg/L), ceftaroline (MIC ≤2 mg/L), rifampicin, and mupirocin but were resistant to erythromycin (21.3%), clindamycin (14.0%), gentamicin (3.8%), kanamycin (10.5%), fusidic acid (27.0%), tetracycline (6.9%), trimethoprim (23.1%), and ciprofloxacin (35.2%). Molecular typing identified 155 spa types, dominated by t127 (15.0%), t084 (5.4%), t3841 (5.4%), t267 (2.4%), t442 (2.2%), t091 (2.2%), t021 (2.2%), and t003 (2.2%); 31 clonal complexes (CCs); and 56 sequence types (STs). The majority of the isolates (n = 265; 59.4%) belonged to CC1 (20.6%), CC15 (10.9%), CC22 (5.1%), CC30 (7.6%), CC361 (10.1%), and CC398 (4.7%). The MSSA isolates belonged to diverse genetic backgrounds dominated by CC1, CC15, CC22, CC30, CC361, and CC398. The distribution of MSSA clones in 2016 and 2021 showed the stability of these clones over time. The study provides the first comprehensive data on the clonal distribution of MSSA in Kuwait hospitals.

Genomic Comparative of Pseudomonas aeruginosa Small Colony Variant, Mucoid and Non-mucoid Phenotypes Obtained from a Patient with Cystic Fibrosis During Respiratory Exacerbations.

Pseudomonas aeruginosa, the most prevalent opportunistic pathogen in chronic obstructive pulmonary disease, associated with high morbidity and mortality in patients with cystic fibrosis (CF), is practically impossible to be eradicated from the airways in chronicity. Its extraordinary genomic plasticity is possibly associated with high antimicrobial resistance, virulence factors, and its phenotypic diversity. The occurrence of P. aeruginosa isolates promoting airway infection, showing mucoid, non-mucoid, and small colony variant (SCV) phenotypes, was observed simultaneously, in the present study, in sputum cultures obtained from a male CF young patient with chronic pulmonary infection for over a decade. The isolates belonged to a new ST (2744) were obtained in two moments of exacerbation of the respiratory disease, in which he was hospitalized. Genetic background and phenotypic analysis indicated that the isolates exhibited multi- and pan-antimicrobial resistant profiles, as well as non-susceptible to polymyxin and predominantly hypermutable (HPM) phenotypes. Whole genome sequencing showed variations in genome sizes, coding sequences and their determinants of resistance and virulence. The annotated genomes were compared for antimicrobial resistance, hypermutability, and SCV characteristics. We highlight the lack of reported genetic determinants of SCV emergence and HPM phenotypes, which can be explained in part due to the very short time between collections of isolates. To the best of our knowledge, this is the first report of genome sequencing of P. aeruginosa SCV from a CF patient in Brazil.

Anti-IL23/12 agents and JAK inhibitors for inflammatory bowel disease.

IBD (inflammatory bowel disease) is a chronic inflammatory disease of the gastrointestinal tract with increasing incidence worldwide. Multiple factors, such as genetic background, environmental and luminal factors, and mucosal immune dysregulation, have been implicated in the cause of IBD, although the cause of the disease remains unknown. IL-12 and IL-23 and their downstream signaling pathways participate in the pathogenesis of inflammatory bowel disease. Early and aggressive treatment with biologic therapies or novel small molecules is needed to decrease complications and the need for hospitalization and surgery. The landscape of inflammatory bowel disease (IBD) treatment has tremendously improved with the development of biologics and small molecule drugs. Several novel biologics and small molecule drugs targeting IL-12 and IL-23 and their downstream targets have shown positive efficacy and safety data in clinical trials, and several drugs have been approved for the treatment of IBD. In the future, numerous potential emerging therapeutic options for IBD treatment are believed to come to the fore, achieving disease cure.

Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations.

Mortality is an economically important trait usually handled as a discrete outcome from hatch time until selection in most broiler breeder programs. However, in other species, it has been shown that not only does the genetic component change over time, but there are maternal genetic effects to be considered when mortality is recorded early in life. This study aimed to investigate alternative trait definitions of mortality with varying models and effects. Three years' worth of data were provided by Cobb-Vantress, Inc. and included two mortality traits. The first trait was binary, whether the bird died or not (OM), and the second trait was a categorical weekly mortality trait (WM). After data cleaning, six weeks of data for the two given mortality traits were used to develop five additional trait definitions. The definitions were broiler mortality (BM), early and late mortality (EM & LM), and two traits with repeated records as cumulative or binary (CM and RM, respectively). Variance components were estimated using linear and threshold models to investigate whether either model had a benefit. Genomic breeding values were predicted using the BLUP90 software suite, and linear regression validation (LR) was used to compare trait definitions and models. Heritability estimates ranged from 0.01 (0.00) to 0.16 (0.01) under linear and 0.04 (0.01) to 0.21 (0.01) under threshold models, indicating genetic variability within the population across these trait definitions. The genetic correlation between EM and LM ranged from 0.48 to 0.81 across the different lines, indicating they have divergent genetic backgrounds and should be considered different traits. The LR accuracies showed that EM and LM used together in a two-trait model have comparable accuracies to that of OM while giving a more precise picture of mortality. When including the maternal effect, the direct heritability considerably decreased for EM, indicating that the maternal effect plays an important role in early mortality. Therefore, a suitable approach would be a model with EM and LM while considering the maternal effect for EM. Single nucleotide polymorphism effects were estimated, and no individual SNP explained more than 1% of the additive genetic variance. Additionally, the SNP with the largest effect size and variance were inconsistent across trait definitions. Chicken mortality can be defined in different ways, and reviewing these definitions and models may benefit poultry breeding programs.

Molecular dissection of cobra venom highlights heparinoids as an antidote for spitting cobra envenoming.

Snakebites affect about 1.8 million people annually. The current standard of care involves antibody-based antivenoms, which can be difficult to access and are generally not effective against local tissue injury, the primary cause of morbidity. Here, we used a pooled whole-genome CRISPR knockout screen to define human genes that, when targeted, modify cell responses to spitting cobra venoms. A large portion of modifying genes that conferred resistance to venom cytotoxicity was found to control proteoglycan biosynthesis, including EXT1, B4GALT7, EXT2, EXTL3, XYLT2, NDST1, and SLC35B2, which we validated independently. This finding suggested heparinoids as possible inhibitors. Heparinoids prevented venom cytotoxicity through binding to three-finger cytotoxins, and the US Food and Drug Administration-approved heparinoid tinzaparin was found to reduce tissue damage in mice when given via a medically relevant route and dose. Overall, our systematic molecular dissection of cobra venom cytotoxicity provides insight into how we can better treat cobra snakebite envenoming.

Towards an enhanced understanding of osteoanabolic effects of PTH-induced microRNAs on osteoblasts using a bioinformatic approach.

In this study, we used a bioinformatic approach to construct a miRNA-target gene interaction network potentially involved in the anabolic effect of parathyroid hormone analogue teriparatide [PTH (1-34)] on osteoblasts. We extracted a dataset of 26 microRNAs (miRNAs) from previously published studies and predicted miRNA target interactions (MTIs) using four software tools: DIANA, miRWalk, miRDB, and TargetScan. By constructing an interactome of PTH-regulated miRNAs and their predicted target genes, we elucidated signaling pathways regulating pluripotency of stem cells, the Hippo signaling pathway, and the TGF-beta signaling pathway as the most significant pathways in the effects of PTH on osteoblasts. Furthermore, we constructed intersection of MTI networks for these three pathways and added validated interactions. There are 8 genes present in all three selected pathways and a set of 18 miRNAs are predicted to target these genes, according to literature data. The most important genes in all three pathways were BMPR1A, BMPR2 and SMAD2 having the most interactions with miRNAs. Among these miRNAs, only miR-146a-5p and miR-346 have validated interactions in these pathways and were shown to be important regulators of these pathways. In addition, we also propose miR-551b-5p and miR-338-5p for further experimental validation, as they have been predicted to target important genes in these pathways but none of their target interactions have yet been verified. Our wet-lab experiment on miRNAs differentially expressed between PTH (1-34) treated and untreated mesenchymal stem cells supports miR-186-5p from the literature obtained data as another prominent miRNA. The meticulous selection of miRNAs outlined will significantly support and guide future research aimed at discovering and understanding the crucial pathways of osteoanabolic PTH-epigenetic effects on osteoblasts. Additionally, they hold potential for the discovery of new PTH target genes, innovative biomarkers for the effectiveness and safety of osteoporosis-affected treatment, as well as novel therapeutic targets.