Bioinformatics Methods Research Articles

Bioinformatics and system biology approaches to determine the connection of SARS-CoV-2 infection and intrahepatic cholangiocarcinoma.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide, which poses a severe threat to human health. COVID-19 is a systemic ailment affecting various tissues and organs, including the lungs and liver. Intrahepatic cholangiocarcinoma (ICC) is one of the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. Nonetheless, few studies have investigated the impact of COVID-19 on ICC patients. With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC, and searched for potential therapeutic drugs. This study identified a total of 70 common differentially expressed genes (DEGs) shared by both diseases, shedding light on their shared functionalities. Enrichment analysis pinpointed metabolism and immunity as the primary areas influenced by these common genes. Subsequently, through protein-protein interaction (PPI) network analysis, we identified SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1 as hub genes. Additionally, 44 transcription factors (TFs) and 112 microRNAs (miRNAs) were forecasted to regulate the hub genes. Most importantly, several drug candidates (Periodate-oxidized adenosine, Desipramine, Quercetin, Perfluoroheptanoic acid, Tetrandrine, Pentadecafluorooctanoic acid, Benzo[a]pyrene, SARIN, Dorzolamide, 8-Bromo-cAMP) may prove effective in treating ICC and COVID-19. This study is expected to provide valuable references and potential drugs for future research and treatment of COVID-19 and ICC.

Genome-Wide Analysis Elucidates the Roles of GhTIR1/AFB Genes Reveals the Function of Gh_D08G0763 (GhTIR1) in Cold Stress in G. hirsutum.

This study identified 13 GhTIR1/AFB members in G. hirsutum through bioinformatics methods and divided them into three subgroups by phylogenetic tree analysis. Motif and gene structure analysis showed that the genes in this family were highly conserved. Promoter cis-acting element analysis found that the promoters of GhTIR1/AFBs contained a large number of cis-acting elements in response to growth and development and abiotic stress. Further RT-qPCR results showed that GhTIR1/AFB genes responded to various abiotic stresses such as IAA, ABA, cold, and heat, and the expression levels of each gene changed obviously, especially Gh_D08G0763 (GhTIR1), which responded significantly to cold injury. Using VIGS (virus-induced gene silencing) technology to silence Gh_D08G0763 in the cold-tolerant cotton variety ZM36, it was found that the resistance of ZM36 to cold damage was significantly reduced. The physiological response mechanism of the Gh_D08G0763 in resisting cold damage was further analyzed through trypan blue staining of leaves and determination of enzyme activity levels. This study provided effective genetic resources for cotton cold-tolerance breeding.

AAT resistance-related AC007405.2 and AL354989.1 as novel diagnostic and prognostic markers in prostate cancer.

Prostate cancer (PCa) is the second disease threatening men's health, and anti-androgen therapy (AAT) is a primary approach for treating this condition. Increasing evidence suggests that long non-coding RNAs (lncRNAs) play crucial roles in the development of PCa and the process of AAT resistance. The objective of this study is to utilize bioinformatics methods to excavate lncRNAs association with AAT resistance and investigate their biological functions. AAT resistance-related risk score model (ARR-RSM) was established by multivariate Cox analysis. Paired clinical tissue samples of 36 PCa patients and 42 blood samples from patients with PSA over 4 ng/ml were collected to verify the ARR-RSM. In vitro, RT-qPCR, CCK-8 and clone formation assays were displayed to verify the expression and function of AL354989.1 and AC007405.2. Pearson correlation analysis identified 996 lncRNAs were associated with AAT resistance (ARR-LncRs). ARR-RSM was established using multivariate Cox regression analysis, and PCa patients were divided into high-risk and low-risk groups. High-risk patients showed increased expression of AL354989.1 and AC007405.2 had poorer prognoses. The high-risk score correlated with advanced T-stage and N-stage. The AUC of ARR-RSM outperformed tPSA in diagnosing PCa. Silencing of AC007405.2 and AL354989.1 inhibited PCa cells proliferation and AAT resistance. In this study, we have discovered the clinical significance of AC007405.2 and AL354989.1 in predicting the prognosis and diagnosing PCa patients. Furthermore, we have confirmed their correlation with various clinical features. These findings provide potential targets for PCa treatment and a novel diagnostic and predictive indicator for precise PCa diagnosis.

Measuring, visualizing, and diagnosing reference bias with biastools

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor’s variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.

Design and construction of a phage-displayed Camelid nanobody library using a simple bioinformatics method

BackgroundRational design of synthetic phage-displayed libraries requires the identification of the most appropriate positions for randomization using defined amino acid sets to recapitulate the natural occurrence. The present study uses position-specific scoring matrixes (PSSMs) for identifying and randomizing Camelidae nanobody (VHH) CDR3. The functionality of a synthetic VHH repertoire designed by this method was tested for discovering new VHH binders to recombinant coagulation factor VII (rfVII). MethodsBased on PSSM analysis, the CDR3 of cAbBCII10 VHH framework was identified, and a set of amino acids for the substitution of each PSSM-CDR3 position was defined. Using the Rosetta design SwiftLib tool, the final repertoire was back-translated to a degenerate nucleotide sequence. A synthetic phage-displayed library was constructed based on this repertoire and screened for anti-rfVII binders. ResultsA synthetic phage-displayed VHH library with 1 × 108 variants was constructed. Three VHH binders to rfVII were isolated from this library with estimated dissociation constants (KD) of 1 × 10−8 M, 5.8 × 10−8 M and 2.6 × 10-7 M. ConclusionPSSM analysis is a simple and efficient way to design synthetic phage-displayed libraries.

Genome-wide identification and stress response analysis of BcaCPK gene family in amphidiploid Brassica carinata.

Calcium-dependent protein kinases (CPKs) are crucial for recognizing and transmitting Ca2+ signals in plant cells, playing a vital role in growth, development, and stress response. This study aimed to identify and detect the potential roles of the CPK gene family in the amphidiploid Brassica carinata (BBCC, 2n = 34) using bioinformatics methods. Based on the published genomic information of B. carinata, a total of 123 CPK genes were identified, comprising 70 CPK genes on the B subgenome and 53 on the C subgenome. To further investigate the homologous evolutionary relationship between B. carinata and other plants, the phylogenetic tree was constructed using CPKs in B. carinata and Arabidopsis thaliana. The phylogenetic analysis classified 123 family members into four subfamilies, where gene members within the same subfamily exhibited similar conserved motifs. Each BcaCPK member possesses a core protein kinase domain and four EF-hand domains. Most of the BcaCPK genes contain 5 to 8 introns, and these 123 BcaCPK genes are unevenly distributed across 17 chromosomes. Among these BcaCPK genes, 120 replicated gene pairs were found, whereas only 8 genes were tandem duplication, suggesting that dispersed duplication mainly drove the family amplification. The results of the Ka/Ks analysis indicated that the CPK gene family of B. carinata was primarily underwent purification selection in evolutionary selection. The promoter region of most BcaCPK genes contained various stress-related cis-acting elements. qRT-PCR analysis of 12 selected CPK genes conducted under cadmium and salt stress at various points revealed distinct expression patterns among different family members in response to different stresses. Specifically, the expression levels of BcaCPK2.B01a, BcaCPK16.B02b, and BcaCPK26.B02 were down-regulated under both stresses, whereas the expression levels of other members were significantly up-regulated under at least one stress. This study systematically identified the BcaCPK gene family in B. carinata, which contributes to a better understanding the CPK genes in this species. The findings also serve as a reference for analyzing stress responses, particularly in relation to cadmium and salt stress in B. carinata.

Isolation and Characterization of the Sulfate Transporter Gene Family and Its Expression Pattern in Response to Selenium and Abiotic Stress in Walnuts (Juglans regia L.)

The sulfate transporter (SULTR) is responsible for the transport and uptake of sulfate, which plays an indispensable role in the growth cycle of plants and adaptation to plant stress. However, there are few reports on the response and regulation of SULTR gene family members in walnuts (Juglans regia L.) to sodium selenate, low temperatures, high temperatures, and simulated drought stress. In this study, the whole genome of the SULTR genes family in walnuts was identified and analyzed by the bioinformatics method. The results show that the walnut genome contains seventeen JrSULTR genes, which are unevenly distributed on eight chromosomes and can be divided into four subfamilies. Cis-acting elements that respond to stress and participate in the regulation of plant hormones were found in the promoter sequence of the JrSULTR genes. The analysis of transcriptome data showed that the expression of JrSULTR1.2b was significantly upregulated under sodium selenate treatment, and the results of qRT-PCR analysis were basically consistent with the transcriptome data. The expression of JrSULTR3.1a and JrSULTR3.4b increased with the prolongation of simulated drought stress time. The transcription levels of JrSULTR1.2b and JrSULTR3.1a were significantly increased after low-temperature treatment. After 9 h of high-temperature treatment, the expression levels of JrSULTR3.1a and JrSULTR3.3 were significantly increased. JrSULTR1.2b and JrSULTR3.1a showed significant expression specificity under stress treatment. At the same time, we also performed subcellular localization of these two genes, which was consistent with the predicted results and was in the cell membrane, and their regulatory functions need to be further studied. These studies laid the foundation for us to explore the specific function of the JrSULTR genes in alleviating abiotic stress in walnuts.

Genome-Wide Identification of Calmodulin-Binding Protein 60 Gene Family and the Function of GhCBP60B in Cotton Growth and Development and Abiotic Stress Response.

The calmodulin-binding protein 60 (CBP60) family is a gene family unique to plants, and its members play a crucial role in plant defense responses to pathogens and growth and development. Considering that cotton is the primary source of natural cotton textile fiber, the functional study of its CBP60 gene family members is critical. In this research, we successfully identified 162 CBP60 members from the genomes of 21 species. Of these, 72 members were found in four cotton species, divided into four clades. To understand the function of GhCBP60B in cotton in depth, we conducted a detailed analysis of its sequence, structure, cis-acting elements, and expression patterns. Research results show that GhCBP60B is located in the nucleus and plays a crucial role in cotton growth and development and response to salt and drought stress. After using VIGS (virus-induced gene silencing) technology to conduct gene silencing experiments, we found that the plants silenced by GhCBP60B showed dwarf plants and shortened stem nodes, and the expression of related immune genes also changed. In further abiotic stress treatment experiments, we found that GhCBP60B-silenced plants were more sensitive to drought and salt stress, and their POD (peroxidase) activity was also significantly reduced. These results imply the vital role of GhCBP60B in cotton, especially in regulating plant responses to drought and salt stress. This study systematically analyzed CBP60 gene family members through bioinformatics methods and explored in depth the biological function of GhCBP60B in cotton. These research results lay a solid foundation for the future use of the GhCBP60B gene to improve cotton plant type and its drought and salt resistance.

Using Sequence Analyses to Quantitatively Measure Oropharyngeal Swallowing Temporality in Point-of-Care Ultrasound Examinations: A Pilot Study.

(1) Background: Swallowing is a complex process that comprises well-timed control of oropharyngeal and laryngeal structures to achieve airway protection and swallowing efficiency. To understand its temporality, previous research adopted adherence measures and revealed obligatory pairs in healthy swallows and the effect of aging and bolus type on the variability of event timing and order. This study aimed to (i) propose a systemic conceptualization of swallowing physiology, (ii) apply sequence analyses, a set of information-theoretic and bioinformatic methods, to quantify and characterize swallowing temporality, and (iii) investigate the effect of aging and dysphagia on the quantified variables using sequence analyses measures. (2) Method: Forty-three participants (17 young adults, 15 older adults, and 11 dysphagic adults) underwent B-mode ultrasound swallowing examinations at the mid-sagittal plane of the submental region. The onset, maximum, and offset states of hyoid bone displacement, geniohyoid muscle contraction, and tongue base retraction were identified and sorted to form sequences which were analyzed using an inventory of sequence analytic techniques; namely, overlap coefficients, Shannon entropy, and longest common subsequence algorithms. (3) Results: The concurrency of movement sequence was found to be significantly impacted by aging and dysphagia. Swallowing sequence variability was also found to be reduced with age and the presence of dysphagia (H(2) = 52.253, p < 0.001, η2 = 0.260). Four obligatory sequences were identified, and high adherence was also indicated in two previously reported pairs. These results provided preliminary support for the validity of sequence analyses for quantifying swallowing sequence temporality. (4) Conclusions: A systemic conceptualization of human deglutition permits a multi-level quantitative analysis of swallowing physiology. Sequence analyses are a set of promising quantitative measurement techniques for point-of-care ultrasound (POCUS) swallowing examinations and outcome measures for swallowing rehabilitation and evaluation of associated physiological conditions, such as sarcopenia. Findings in the current study revealed physiological differences among healthy young, healthy older, and dysphagic adults. They also helped lay the groundwork for future AI-assisted dysphagia assessment and outcome measures using POCUSs. Arguably, the proposed conceptualization and analyses are also modality-independent measures that can potentially be generalized for other instrumental swallowing assessment modalities.

Research progress on bioinformatics in pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a severe disease characterized by abnormal pulmonary vascular remodeling and increased right ventricular pressure load, posing a significant threat to patient health. While some pathological mechanisms of PAH have been revealed, the deeper mechanisms of pathogenesis remain to be elucidated. In recent years, bioinformatics has provided a powerful tool for a deeper understanding of the complex mechanisms of PAH through the integration of techniques such as multi-omics analysis, artificial intelligence, and Mendelian randomization. This review focuses on the bioinformatics methods and technologies used in PAH research, summarizing their current applications in the study of disease mechanisms, diagnosis, and prognosis assessment. Additionally, it analyzes the existing challenges faced by bioinformatics and its potential applications in the clinical and basic research fields of PAH in the future.

Correlation between Mitochondria-Associated Endoplasmic Reticulum Membrane-Related Genes and Cellular Senescence-Related Genes in Osteoarthritis.

The role of mitochondria-associated endoplasmic reticulum membrane (MAM) formation in the development of osteoarthritis (OA) is yet unclear. A mix of bioinformatics methods and in vitro experimental methodologies was used to study and corroborate the role of MAM-related genes and cellular senescence-related genes in the development of OA. The Gene Expression Omnibus database was used to obtain the microarray information that is relevant to the OA. Several bioinformatic methods were employed to carry out function enrichment analysis and protein-protein correlation analysis, build the correlation regulatory network, and investigate potential relationships between MAM-related genes and cellular senescence-related genes in OA. These methods also served to identify the MAM-related and OA-related genes (MAM-OARGs). For the additional functional enrichment analysis, a total of 13 MAM-OARGs were detected. The correlation regulatory network was also created. Hub MAM-OARGs were shown to have a strong correlation with genes relevant to cellular senescence in OA. Results of in vitro experiments further demonstrated a positive correlation between MAM-OARGs (PTPN1 and ITPR1) and cellular senescence-related and OA-related genes. As a result, our findings can offer new insights into the investigations of MAM-related genes and cellular senescence-related genes, which could be linked to the OA as well as brand-new potential treatment targets.

Identification of a robust biomarker LAPTM4A for glioma based on comprehensive computational biology and experimental verification.

Glioma, a highly invasive and deadly form of human neoplasm, presents a pressing need for the exploration of potential therapeutic targets. While the lysosomal protein transmembrane 4A (LATPM4A) has been identified as a risk factor in pancreatic cancer patients, its role in glioma remains unexplored. The analysis of differentially expressed genes (DEG) was conducted from The Cancer Genome Atlas (TCGA) glioma dataset and the Genotype Tissue Expression (GTEx) dataset. Through weighted gene co-expression network analysis (WGCNA), the key glioma-related genes were identified. Among these, by using Kaplan-Meier (KM) analysis and univariate/multivariate COX methods, LAPTM4A emerged as the most influential gene. Moreover, the bioinformatics methods and experimental verification were employed to analyze its relationships with diagnosis, clinical parameters, epithelial-mesenchymal transition (EMT), metastasis, immune cell infiltration, immunotherapy, drug sensitivity, and ceRNA network. Our findings revealed that LAPTM4A was up-regulated in gliomas and was associated with clinicopathological features, leading to poor prognosis. Furthermore, functional enrichment analysis demonstrated that LATPM4A played a role in the immune system and cancer progression. In vitro experiments indicated that LAPTM4A may influence metastasis through the EMT pathway in glioma. Additionally, we found that LAPTM4A was associated with the tumor microenvironment (TME) and immunotherapy. Notably, drug sensitivity analysis revealed that patients with high LAPTM4A expression were sensitive to doxorubicin, which contributed to a reduction in LAPTM4A expression. Finally, we uncovered the FGD5-AS1-hsa-miR-103a-3p-LAPTM4A axis as a facilitator of glioma progression. In conclusion, our study identifies LATPM4A as a promising biomarker for prognosis and immune characteristics in glioma.

Biosynthesis of Macrocyclic Peptides with C-Terminal β-Amino-α-keto Acid Groups by Three Different Metalloenzymes.

Advances in genome sequencing and bioinformatics methods have identified a myriad of biosynthetic gene clusters (BGCs) encoding uncharacterized molecules. By mining genomes for BGCs containing a prevalent peptide-binding domain used for the biosynthesis of ribosomally synthesized and post-translationally modified peptides (RiPPs), we uncovered a new compound class involving modifications installed by a cytochrome P450, a multinuclear iron-dependent non-heme oxidative enzyme (MNIO, formerly DUF692), a cobalamin- and radical S-adenosyl-l-methionine-dependent enzyme (B12-rSAM), and a methyltransferase. All enzymes were functionally expressed in Burkholderia sp. FERM BP-3421. Structural characterization demonstrated that the P450 enzyme catalyzed the formation of a biaryl C-C cross-link between two Tyr residues with the B12-rSAM generating β-methyltyrosine. The MNIO transformed a C-terminal Asp residue into aminopyruvic acid, while the methyltransferase acted on the β-carbon of this α-keto acid. Exciton-coupled circular dichroism spectroscopy and microcrystal electron diffraction (MicroED) were used to elucidate the stereochemical configuration of the atropisomer formed upon biaryl cross-linking. To the best of our knowledge, the MNIO featured in this pathway is the first to modify a residue other than Cys. This study underscores the utility of genome mining to isolate new macrocyclic RiPPs biosynthesized via previously undiscovered enzyme chemistry.

Bioinformatics analysis and experimental verification of NLRX1 as a prognostic factor for esophageal squamous cell carcinoma.

Nucleotide binding and oligomeric domain-like receptor X1 (NLRX1), a member of the NLR family, is associated with the physiological and pathological processes of inflammation, autophagy, immunity, metabolism and mitochondrial regulation, and has been demonstrated to have pro- or antitumor effects in various tumor types. However, the biological function of NLRX1 in esophageal squamous cell carcinoma (ESCC) has remained elusive. In the present study, by using bioinformatics methods, the differential expression of NLRX1 at the mRNA level was examined. Overall survival, clinical correlation, receiver operating characteristic curve, Cox regression, co-expression, enrichment, immune infiltration and drug sensitivity analyses were carried out. A nomogram and a calibration curve were constructed. Changes in protein expression levels were investigated by immunohistochemistry and western blotting. The impact of NLRX1 on i) cell proliferation was evaluated by Cell Counting Kit-8 assays; ii) migration was examined by wound-healing assays; iii) migration and invasion were evaluated by Transwell assays; and iv) apoptosis was assessed by Annexin V/PI staining and flow cytometry. The results revealed that, compared to normal adjacent tissue, NLRX1 was lowly expressed in ESCC, and patients with low NLRX1 expression had a shorter survival time. NLRX1 was an independent prognostic factor for ESCC and was associated with tumor grading. Patients in the low-NLRX1 group showed a decrease in the infiltration of activated natural killer cells, monocytes and M0 macrophages, and these immune-cell infiltration levels were positively correlated with NLRX1 expression. Knocking down NLRX1 promoted the proliferation of KYSE450 cells, while overexpression of NLRX1 inhibited the proliferation of ECA109 cells. NLRX1 negatively regulated the PI3K/AKT signaling pathway in ESCC. These findings indicate that, through several mechanisms, NLRX1 suppresses tumor growth in ESCC, which offers new insight for investigating the causes and progression of ESCC, as well as for identifying more efficient therapeutic approaches.

The Impact of Psychological Health on Childhood Obesity: A Cross-Developmental Stage Analysis

This research ventures into the critical public health challenge of childhood obesity by exploring the dynamic interplay between psychological well-being and Body Mass Index (BMI) throughout various developmental stages of childhood. It delves into how emotional regulation, attachment dynamics, and social relationships correlate with obesity from early childhood to adolescence. Highlighting key findings, such as the negative correlation between psychological resilience and higher BMI in young children, the impact of social relationships on obesity risk during pre-adolescence, and the link between adaptive emotional strategies and higher BMI in adolescents, this study brings to the fore the nuanced relationship between psychological factors and obesity. Psychological metrics in this study were obtained via referenced questionnaires, leading up to the utilization of the interdisciplinary process of bioinformatics. Utilizing the interdisciplinary process of bioinformatics, this research synergizes psychometric and biomedical data to unearth psychological markers critical for crafting targeted, age-appropriate interventions. This study advocates for a holistic healthcare approach, emphasizing the integration of psychological support within obesity prevention and management strategies, thereby underscoring the indispensable role of psychological factors in the fight against childhood obesity. The application of bioinformatics methods to analyze complex datasets demonstrates how collaboration across medical specialties can enrich our understanding and response to childhood obesity, contributing significantly to the development of comprehensive, bioinformatics-enhanced healthcare solutions.

Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning.

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor. Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs. Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML. Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

Analysis of clinical characteristics of infections caused by Shewanella species

PurposeThe Shewanella genus is a rare pathogen of marine origin. In recent years, there has been a continuous increase in infection cases caused by this bacterium, and we have observed the uniqueness of infections caused by this microorganism. Materials and methodsThis study conducted a retrospective analysis of the medical history and laboratory examination data of patients infected with the Shewanella genus over the past decade. Additionally, it employed bioinformatics methods to analyze the relevant virulence factors and antibiotic resistance genes associated with the Shewanella genus. ResultsOver the past 10 years, we have isolated 51 cases of Shewanella, with 68.82% being Shewanella putrefaciens (35/51 cases) and 31.37% being Shewanella algae (16/51 cases). Infected individuals often had underlying diseases, with 39.22% (20/51) having malignant tumors and 25.49% (13/51) having liver and biliary system diseases primarily characterized by stones. The majority of patients, 62.74% (32/51), exhibited mixed infections, including one case with a combination of infections from three other types of bacteria and five cases with a combination of infections from two other types of bacteria. The identified microorganisms were commonly resistant to ticarcillin-clavulanic acid (23.5%), followed by cefoperazone-sulbactam (19.6%), ciprofloxacin (17.6%), and cefotaxime (17.6%). Bioinformatics analysis indicates that Shewanella can express bile hydrolysis regulators and fatty acid metabolism regulators that aid in adapting to the unique environment of the biliary tract. Additionally, it expresses abundant catalase, superoxide dismutase, and two-component signal transduction system proteins, which may be related to environmental adaptation. Shewanella also expresses various antibiotic resistance genes, including beta-lactamases and aminoglycoside modification enzymes. Iron carriers may be one of its important virulence factors. ConclusionsWe speculate that the Shewanella genus may exist as a specific colonizer in the human body, and under certain conditions, it may act as a pathogen, leading to biliary infections in the host.

Functional characterization of plant specific Indeterminate Domain (IDD) transcription factors in tomato (Solanum lycopersicum L.)

Plant-specific transcription factors (TFs) are responsible for regulating the genes involved in the development of plant-specific organs and response systems for adaptation to terrestrial environments. This includes the development of efficient water transport systems, efficient reproductive organs, and the ability to withstand the effects of terrestrial factors, such as UV radiation, temperature fluctuations, and soil-related stress factors, and evolutionary advantages over land predators. In rice and Arabidopsis, INDETERMINATE DOMAIN (IDD) TFs are plant-specific TFs with crucial functions, such as development, reproduction, and stress response. However, in tomatoes, IDD TFs remain uncharacterized. Here, we examined the presence, distribution, structure, characteristics, and expression patterns of SlIDDs. Database searches, multiple alignments, and motif alignments suggested that 24 TFs were related to Arabidopsis IDDs. 18 IDDs had two characteristic C2H2 domains and two C2HC domains in their coding regions. Expression analyses suggest that some IDDs exhibit multi-stress responsive properties and can respond to specific stress conditions, while others can respond to multiple stress conditions in shoots and roots, either in a tissue-specific or universal manner. Moreover, co-expression database analyses suggested potential interaction partners within IDD family and other proteins. This study functionally characterized SlIDDs, which can be studied using molecular and bioinformatics methods for crop improvement.

Resveratrol regulates Thoc5 to improve maternal immune activation-induced autism-like behaviors in adult mouse offspring

Maternal infection during pregnancy is an important cause of autism spectrum disorder (ASD) in offspring, and inflammatory infiltration caused by maternal immune activation (MIA) can cause neurodevelopmental disorders in the fetus. Medicine food homologous (MFH) refers to a traditional Chinese medicine (TCM) concept, which effectively combines food functions and medicinal effects. However, no previous study has screened, predicted, and validated the potential targets of MFH herbs for treating ASD. Therefore, in this study, we used comprehensive bioinformatics methods to screen and analyze MFH herbs and drug targets on a large scale, and identified resveratrol and Thoc5 as the best small molecular ingredient and drug target, respectively, for the treatment of MIA-induced ASD. Additionally, the results of in vitro experiments revealed that resveratrol increased the expression of Thoc5 and effectively inhibited lipopolysaccharide-induced inflammatory factor production by BV2 cells. Moreover, in vivo, resveratrol increased the expression of Thoc5 and effectively inhibited placental and fetal brain inflammation in MIA pregnancy mice, and improved ASD-like behaviors in offspring.

Identification of HIST1H2BH as the hub gene associated with multiple myeloma using integrated bioinformatics analysis.

Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy. Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines. A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines. We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.