Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis.

Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism's collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs' gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions.

Effects of Spermine Synthase Deficiency in Mesenchymal Stromal Cells Are Rescued by Upstream Inhibition of Ornithine Decarboxylase.

Despite the well-known relevance of polyamines to many forms of life, little is known about how polyamines regulate osteogenesis and skeletal homeostasis. Here, we report a series of in vitro studies conducted with human-bone-marrow-derived pluripotent stromal cells (MSCs). First, we show that during osteogenic differentiation, mRNA levels of most polyamine-associated enzymes are relatively constant, except for the catabolic enzyme spermidine/spermine N1-acetyltransferase 1 (SAT1), which is strongly increased at both mRNA and protein levels. As a result, the intracellular spermidine to spermine ratio is significantly reduced during the early stages of osteoblastogenesis. Supplementation of cells with exogenous spermidine or spermine decreases matrix mineralization in a dose-dependent manner. Employing N-cyclohexyl-1,3-propanediamine (CDAP) to chemically inhibit spermine synthase (SMS), the enzyme catalyzing conversion of spermidine into spermine, also suppresses mineralization. Intriguingly, this reduced mineralization is rescued with DFMO, an inhibitor of the upstream polyamine enzyme ornithine decarboxylase (ODC1). Similarly, high concentrations of CDAP cause cytoplasmic vacuolization and alter mitochondrial function, which are also reversible with the addition of DFMO. Altogether, these studies suggest that excess polyamines, especially spermidine, negatively affect hydroxyapatite synthesis of primary MSCs, whereas inhibition of polyamine synthesis with DFMO rescues most, but not all of these defects. These findings are relevant for patients with Snyder-Robinson syndrome (SRS), as the presenting skeletal defects-associated with SMS deficiency-could potentially be ameliorated by treatment with DFMO.

PyAGH: a python package to fast construct kinship matrices based on different levels of omic data.

BACKGROUND: Construction of kinship matrices among individuals is an important step for both association studies and prediction studies based on different levels of omic data. Methods for constructing kinship matrices are becoming diverse and different methods have their specific appropriate scenes. However, software that can comprehensively calculate kinship matrices for a variety of scenarios is still in an urgent demand. RESULTS: In this study, we developed an efficient and user-friendly python module, PyAGH, that can accomplish (1) conventional additive kinship matrces construction based on pedigree, genotypes, abundance data from transcriptome or microbiome; (2) genomic kinship matrices construction in combined population; (3) dominant and epistatic effects kinship matrices construction; (4) pedigree selection, tracing, detection and visualization; (5) visualization of cluster, heatmap and PCA analysis based on kinship matrices. The output from PyAGH can be easily integrated in other mainstream software based on users' purposes. Compared with other softwares, PyAGH integrates multiple methods for calculating the kinship matrix and has advantages in terms of speed and data size compared to other software. PyAGH is developed in python and C + + and can be easily installed by pip tool. Installation instructions and a manual document can be freely available from https://github.com/zhaow-01/PyAGH . CONCLUSION: PyAGH is a fast and user-friendly Python package for calculating kinship matrices using pedigree, genotype, microbiome and transcriptome data as well as processing, analyzing and visualizing data and results. This package makes it easier to perform predictions and association studies processes based on different levels of omic data.

Underwater single photon 3D imaging with millimeter depth accuracy and reduced blind range.

Mono-static system benefits from its more flexible field of view and simplified structure, however, the backreflection photons from mono-static system lead to count loss for target detection. Counting loss engender range-blind, impeding the accurate acquisition of target depth. In this paper, count loss is reduced by introducing a polarization-based underwater mono-static single-photon imaging method, and hence reduced blind range. The proposed method exploits the polarization characteristic of light to effectively reduce the count loss of the target, thus improving the target detection efficiency. Experiments demonstrate that the target profile can be visually identified under our method, while the unpolarization system can not. Moreover, the ranging precision of system reaches millimeter-level. Finally, the target profile is reconstructed using non-local pixel correlations algorithm.

Ranging analysis of a moving target based on the dynamic instrument response function.

A ranging high-speed moving target with a high accuracy is challenging for a single-photon ranging system (SPRS). In this Letter, the dynamic instrument response function (IRF) is proposed to establish a dynamic discrete model (DDM) by introducing a velocity and a system timing resolution, which leads to better accuracy of cross-correlation results. And with the data of a dynamic Monte Carlo (DMC), the ranging accuracy can be improved with DDM.

A web tool for the global identification of pig breeds.

BACKGROUND: Natural and artificial selection for more than 9000 years have led to a variety of domestic pig breeds. Accurate identification of pig breeds is important for breed conservation, sustainable breeding, pork traceability, and local resource registration. RESULTS: We evaluated the performance of four selectors and six classifiers for breed identification using a wide range of pig breeds (N = 91). The internal cross-validation and external independent testing showed that partial least squares regression (PLSR) was the most effective selector and partial least squares-discriminant analysis (PLS-DA) was the most powerful classifier for breed identification among many breeds. Five-fold cross-validation indicated that using PLSR as the selector and PLS-DA as the classifier to discriminate 91 pig breeds yielded 98.4% accuracy with only 3K single nucleotide polymorphisms (SNPs). We also constructed a reference dataset with 124 pig breeds and used it to develop the web tool iDIGs ( http://alphaindex.zju.edu.cn/iDIGs_en/ ) as a comprehensive application for global pig breed identification. iDIGs allows users to (1) identify pig breeds without a reference population and (2) design small panels to discriminate several specific pig breeds. CONCLUSIONS: In this study, we proved that breed identification among a wide range of pig breeds is feasible and we developed a web tool for such pig breed identification.

The effect of high-density genotypic data and different methods on joint genomic prediction: A case study in large white pigs.

Joint genomic prediction (GP) is an attractive method to improve the accuracy of GP by combining information from multiple populations. However, many factors can negatively influence the accuracy of joint GP, such as differences in linkage disequilibrium phasing between single nucleotide polymorphisms (SNPs) and causal variants, minor allele frequencies and causal variants' effect sizes across different populations. The objective of this study was to investigate whether the imputed high-density genotype data can improve the accuracy of joint GP using genomic best linear unbiased prediction (GBLUP), single-step GBLUP (ssGBLUP), multi-trait GBLUP (MT-GBLUP) and GBLUP based on genomic relationship matrix considering heterogenous minor allele frequencies across different populations (wGBLUP). Three traits, including days taken to reach slaughter weight, backfat thickness and loin muscle area, were measured on 67 276 Large White pigs from two different populations, for which 3334 were genotyped by SNP array. The results showed that a combined population could substantially improve the accuracy of GP compared with a single-population GP, especially for the population with a smaller size. The imputed SNP data had no effect for single population GP but helped to yield higher accuracy than the medium-density array data for joint GP. Of the four methods, ssGLBUP performed the best, but the advantage of ssGBLUP decreased as more individuals were genotyped. In some cases, MT-GBLUP and wGBLUP performed better than GBLUP. In conclusion, our results confirmed that joint GP could be beneficial from imputed high-density genotype data, and the wGBLUP and MT-GBLUP methods are promising for joint GP in pig breeding.

The construction of a haplotype reference panel using extremely low coverage whole genome sequences and its application in genome-wide association studies and genomic prediction in Duroc pigs.

Extremely low coverage whole genome sequencing (lcWGS) is an economical technique to obtain high-density single nucleotide polymorphisms (SNPs). Here, we explored the feasibility of constructing a haplotype reference panel (lcHRP) using lcWGS and evaluated the effects of lcHRP through a genome-wide association study (GWAS) and genomic prediction in pigs. A total of 297 and 974 Duroc pigs were genotyped using lcWGS and a 50 K SNP array, respectively. We obtained 19,306,498 SNPs using lcWGS with an accuracy of 0.984. With the help of lcHRP, the accuracy of imputation from the SNP array to lcWGS was 0.922. Compared to the SNP array findings, those from the imputation-based GWAS identified more signals across four traits. With the integration of the top 1% imputation-based GWAS findings as genomic features, the accuracies of genomic prediction was improved by 6.0% to 13.2%. This study showed the great potential of lcWGS in pigs' molecular breeding.

The Role of SOCS3 in Regulating Meat Quality in Jinhua Pigs.

Meat quality is an important economic trait that influences the development of the pig industry. Skeletal muscle development and glycolytic potential (GP) are two crucial aspects that significantly impact meat quality. It has been reported that abnormal skeletal muscle development and high glycogen content results in low meat quality. However, the genetic mechanisms underlying these factors are still unclear. Compared with intensive pig breeds, Chinese indigenous pig breeds, such as the Jinhua pig, express superior meat quality characteristics. The differences in the meat quality traits between Jinhua and intensive pig breeds make them suitable for uncovering the genetic mechanisms that regulate meat quality traits. In this study, the Jinhua pig breed and five intensive pig breeds, including Duroc, Landrace, Yorkshire, Berkshire, and Pietrain pig breeds, were selected as experimental materials. First, the FST and XP-EHH methods were used to screen the selective signatures on the genome in the Jinhua population. Then, combined with RNA-Seq data, the study further confirmed that SOCS3 could be a key candidate gene that influences meat quality by mediating myoblast proliferation and glycometabolism because of the down-regulated expression of SOCS3 in Jinhua pigs compared with Landrace pigs. Finally, through SOCS3 knockout (KO) and overexpression (OE) experiments in mouse C2C12 cells, the results showed that SOCS3 regulated the cell proliferation of myoblasts. Moreover, SOCS3 is involved in regulating glucose uptake by the IRS1/PI3K/AKT signaling pathway. Overall, these findings provide a basis for the genetic improvement of meat quality traits in the pig industry.

Efficacy of sternocleidomastoid muscle flap in reducing anastomotic mediastinal/pleural cavity leak.

BACKGROUND: Anastomotic mediastinal/pleural cavity leak (AMPCL) is a life-threatening postoperative complication after esophagectomy. The objective of this study was to find a safe and effective surgical method to reduce the incidence of AMPCL. METHODS: A total of 223 patients who underwent surgery in Fujian Medical University Union Hospital from May 2020 to October 2021 were enrolled in this study. Data for preoperative and postoperative test indices, postoperative complications, perioperative treatment were collected. After using 1:1 propensity score matching (PSM) to match two cohort (caliper = 0.1), the relationship between various factors and the incidence of AMPCL were analyzed. RESULTS: 209 patients were included for further analysis in the end. There were 95 patients in the sternocleidomastoid muscle flap embedding group (intervention group) and 114 in the routine operation group (control group). There was a significant difference in mean age between two groups. Gender, age, body mass index, diabetes, American society of anesthesiologists score, preoperative neoadjuvant therapy, pathological stage were included in performing 1:1 PSM, and there were no significant differences between two groups. Median operative time was significantly less in intervention group. Anastomotic leak (AL) did not present significant difference between two groups (8 [8.6] vs. 13 [14.0], p = 0.247), however, the AMPCL in intervention group was significantly lower than control group (0 [0] vs. 6 [6.5], p = 0.029). CONCLUSIONS: The sternocleidomastoid muscle flap embedding could significantly reduce the incidence of AMPCL. This additional procedure is safe, and effective without increase in the occurrence of postoperative complications and hospital expenses.

First Report of Leaf Blight on Dumasia villosa Caused by Boeremia exigua in China.

Dumasia (Fabaceae, tribe Phaseoleae, subtribe Glycininae), a genus of trifoliate vines, is widely distributed in tropical and subtropical regions of Asia and Africa (Pan & Zhu 2010). In October 2021, lesions were observed on Dumasia villosa leaves on Longwen mountain of Guizhou Normal University, Guiyang City, Guizhou Province, China. The incidence of leaf blight on observed D. villosa leaves was 10%. All necrotic spots were close to insect-feeding sites. Necrotic spots were grey or black, and circular (2 to 10 mm in diameter) or irregular (2 to 20 mm long) in shape. Stems and pods showed no disease symptoms. Pathogen isolation was conducted following surface sterilization with ethanol. After growth for 5 days on potato dextrose agar in a moist climate chamber at 26°C under a 16 h/8 h light/dark cycle, colonies were 5.2 to 5.6 cm in diameter, olivaceous grey in colour, and sparse, white, aerial mycelia with irregular margins were evident. Conidia were hyaline, ellipsoidal to oblong, mostly 1-septate, and occasionally aseptate with dimensions ranging from 3.5 to 7.0 × 1.5 to 3.5 µm (n = 30). To confirm the species of the isolate, ribosomal DNA internal transcribed spacer (ITS) and ß-tubulin (tub2) genes were amplified and sequenced using primers ITS1/ITS4 and Btub2Fd/Btub4Rd (White et al. 1990), respectively. The obtained 529 bp ITS sequence (GenBank accession no. OL872186) shares 99.61% identity with the sequences of Boeremia exigua (MF662797 and GU395499). The obtained 299 bp tub2 sequence (OM830712) shares 100% identity with the sequence of B. exigua (KR653201). Based on morphology and DNA sequence analysis, the isolate was identified as B. exigua. To fulfil Koch's postulates, healthy leaves of 8-week-old D. villosa plants (n = 6) were wounded with a sterilized hypodermic needle and inoculated with 2 µL of a conidial suspension (106 conidia/mL). Six plants were inoculated with 2 µL of sterile distilled water as controls. After 3 days in a moist climate chamber at 26°C under a 16 h/8 h light/dark cycle, dark spots were only present on conidia-inoculated leaves, while controls remained healthy. Boeremia exigua was reisolated from disease spots and confirmed using the same morphological and molecular methods described above. To our knowledge, this is the first report of leaf blight on D. villosa caused by B. exigua, although this fungus has been reported to infect leguminous plants, including field pea (Li et al. 2012), white clover (Wang et al. 2020), and soybean (Schaffrath et al. 2020). In China, B. exigua has also been reported to infect other plants, such as walnut (Cai et al. 2021; Wang et al. 2021) and Japanese ginseng (You et al. 2015). This identification suggests that D. villosa could be a potential reservoir for the pathogen affecting other leguminous crops that might be economically important.

Elsholtzia rugulosa: Phytochemical Profile and Antioxidant, Anti-Alzheimer's Disease, Antidiabetic, Antibacterial, Cytotoxic and Hepatoprotective Activities.

Elsholtzia rugulosa Hemsl., a species of the Labiatae family, has a long history of use as a honey plant, herbal tea, and folk medicine in China. However, little is known about its composition and biological activities. The present study aimed to investigate the total phenol and flavonoid contents, phytochemical composition, and multiple biological activities of this plant. The total flavonoid content of the ethyl acetate fraction (EAF) was higher than those of the petroleum ether fraction (PEF), n-butanol fraction (NBF), and water fraction (WF). The EAF also had much stronger antioxidant, cytotoxic, hepatoprotective, and acetylcholinesterase (AChE) and α-glucosidase inhibitory activities than the PEF, NBF, and WF. More importantly, the IC50 values of the EAF and NBF against α-glucosidase were much lower than that of the positive control acarbose, indicating their potent α-glucosidase inhibitory activities. The isolation of the EAF led to the acquisition of 9 compounds, four of which (ß-daucosterol, methyl rosmarinate, betulinic acid, and oleanolic acid) possessed significant α-glucosidase inhibitory activities. Maltol 6'-O-(5-O-p-coumaroyl)-ß-D-apiofuranosyl-ß-D-glucopyranoside and rosmarinic acid were the major phenolic compounds in the EAF according to the HPLC-DAD analysis. All these findings indicate that the EAF, NBF, and some isolated compounds have the potential to be developed as antidiabetic drugs. Moreover, the dual inhibition of AChE and butyrylcholinesterase (BChE) of certain fractions indicates their potential in the development of anti-Alzheimer's disease drugs. The present study provides a new understanding of the phytochemistry and bioactivity of E. rugulosa.

Safety and feasibility of esophagectomy following combined neoadjuvant immunotherapy and chemotherapy for locally advanced esophageal cancer: a propensity score matching.

OBJECTIVES: This study aims to investigate the efficacy and feasibility of esophagectomy following combined neoadjuvant immunotherapy and chemotherapy for locally advanced esophageal cancer. METHODS: We retrospectively identified patients who were treated with neoadjuvant immunotherapy and chemotherapy (NICT, n = 27) or chemotherapy alone (NCT, n = 95) at our institution between January, 2017 and April, 2021. The primary end point was 30-day complications. Major complications were defined as Clavien-Dindo classification grade ≥ 3. Secondary end points were interval to surgery, operation time, postoperative thoracic drainage, thoracic drainage tube stay, 30-day readmission rate, and 30-day mortality. Propensity score matching (PSM) was used to reduce bias caused by potential confounding. RESULTS: All patients included successfully completed neoadjuvant therapy and underwent McKeown minimally invasive esophagectomy negative margins. Out of 122 eligible patients, 26 patients in NICT group and 52 patients in NCT group were identified by 1:2 PSM. After PSM, the clinical stage was matched and demographic characteristics of the two groups were well balanced, including age, gender, BMI, ASA status, age-adjusted Charlson index, smoking, drinking, chemotherapy regimens, neoadjuvant cycle, tumor location, lymphadenectomy, pathological stage, histologic sub-type, anastomotic position, route of gastric conduit, procedure type, and operative approach were comparable between groups after PSM. Although NICT group had a higher incidence of pneumonia and pleural effusion, however, the CCI index, other complication and major complications were comparable between the two groups. There were no significant differences in operation time, intraoperative blood loss, thoracic drainage tube stays, thoracic drainage volume, ICU stay, postoperative hospital stay and hospital cost. Furthermore, 30-day mortality, 30-day readmission, ICU readmission were similar in both groups. CONCLUSIONS: Based on our preliminary experience, esophagectomy is safe and feasible following combined neoadjuvant immunotherapy with chemotherapy for locally advanced esophageal cancer.

Long intergenic non-coding RNA Linc00485 promotes lung cancer progression by modulating miR-298/c-Myc axis.

Long non-coding RNAs (lncRNAs), which are non-protein-coding transcripts, are emerging as novel biomarkers for cancer diagnosis. Their dysregulation is increasingly recognized to contribute to the development and progression of human cancers, including lung cancer. Linc00485 is a newly discovered cancer-related lncRNA; however, little is known about its role in lung cancer progression. In this study, we found that the expression of Linc00485 was significantly increased in human lung cancer tissue and associated with malignant phenotypes, including tumour-node-metastasis (TNM) stage, metastasis and relapse. Furthermore, the proliferative, migratory and invasive abilities of lung cancer cells in vitro were significantly enhanced by overexpression of Linc00485 but inhibited by its silencing. Mechanistically, Linc00485 regulated the expression of c-Myc by directly binding to miR-298; the effects of Linc00485 overexpression could be significantly reversed by a c-Myc inhibitor or small interfering RNA. Xenotransplantation experiments showed that Linc00485 silencing significantly weakened the proliferation potential of A549 cells in vivo. Overall, these findings indicate that Linc00485 overexpression down-regulates miR-298, resulting in the up-regulation of c-Myc and thereby promoting the development of lung cancer.

Synergistic effects of D-arginine, D-methionine and D-histidine against Porphyromonas gingivalis biofilms.

Porphyromonas gingivalis biofilms are implicated in the pathology of peri-implantitis and periodontitis. In this study, D-arginine (R), D-methionine (M), D-histidine (H), and a mixture of these D-amino acids (D-AAs) were investigated as an effective therapeutic strategy against P. gingivalis biofilms. The bacterial growth activity and minimum inhibitory concentrations were determined for each D-AA, along with the effects of the D-AAs mixture on biofilm development, morphology, structure, extracellular polysaccharides (EPS), cytotoxicity towards commensals, and bacterial structure. The D-AA mixture delayed the proliferation of P. gingivalis, changed its membrane structure, and decreased biofilm thickness and integrity, as compared with individual D-AAs. The EPS content increased with the concentration of D-AAs. The present study shows that a 4 mM RMH, triple D-AA mixture, enhanced deleterious effects on P. gingivalis biofilms without any cytotoxicity compared with individual D-AAs, thus providing a new strategy for the treatment of peri-implantitis and periodontitis.

A Preliminary Study of Antibiotic Resistance Genes in Domestic Honey Produced in China.

Antibiotic resistance genes (ARGs) are emerging contaminants that pose a health risk to humans worldwide. Little information on ARGs in bee honey is available. This study profiles ARGs in bee honey samples produced in China, the biggest producer in the world. Of 317 known ARGs encoding resistance to 8 classes of antibiotics, 212 were found in collected honey samples by a real-time quantitative polymerase chain reaction approach. Occurrence frequencies of genes providing resistance to FCA (fluoroquinolone, quinolone, florfenicol, chloramphenicol, and amphenicol) and aminoglycosides were 21.0% and 18.5%, respectively. Frequencies of genes encoding efflux pumps were 42.5% and those of destructase genes 36.6%, indicating that these two mechanisms were predominant for resistance. Nine plasmid-mediated quinolone resistance genes were detected. Of the nine transposase genes known to be involved in antibiotic resistance, eight were found in the samples examined, with tnpA-4, tnpA-5, and tnpA-6 being more abundant. The abundance of the transposase genes was associated with genes conferring resistance to tetracyclines (r = 0.648, p < 0.01), macrolide-lincosamide-streptogramin B (r = 0.642, p < 0.01), FCA (r = 0.517, p < 0.01), and aminoglycosides (r = 0.401, 0.01 < p < 0.05). This is the first study on the abundance and diversity of ARGs in Chinese bee honey products. These findings suggest that bee honey may be a significant source of ARGs that might pose threat to public health. Further research is required to collect more samples in diverse geographic regions in China to make a more comprehensive judgment of ARG in bee honey.

LGR6 is a potential diagnostic and prognostic marker for esophageal squamous cell carcinoma.

BACKGROUND: Leucine-rich repeat-coupled receptor 6 (LGR6) is a marker of the skin, nails, and other types of adult tissue stem cells and has been widely found to be related to the development and progression of a variety of cancer types. The clinical significance and biological function of LGR6 in esophageal squamous cell carcinoma (ESCC) have not been determined. METHODS: The expression of LGR6 at the transcriptional level was analyzed by searching the TCGA and UCSC data sets. Immunohistochemistry, WB, and q-PCR were used to detect the expression of LGR6 in ESCC and adjacent normal tissues. LGR6 PPI networks and KEGG pathways were used to analyze the potential biological functions of LGR6. RESULTS: The expression of LGR6 in ESCC tissues was significantly higher than that in normal tissues and was negatively correlated with the differentiation degree of ESCC and the prognosis of the patients but not closely correlated with the TNM stage of ESCC. PPI networks showed that LGR6 had a close interaction with RSPO1, RSPO2, RSPO3, and RSPO4. KEGG pathway analysis showed that LGR6 activated the Wnt/ß-catenin signaling pathway by binding with RSPO ligands to promote the progression of ESCC. CONCLUSION: LGR6 can serve as a potential diagnostic and prognostic marker for ESCC.

Transcriptional analysis of impacts of glycerol transporter 1 on methanol and glycerol metabolism in Pichia pastoris.

The efficient promoter of alcohol oxidase 1 (PAOX1) in methylotrophic yeast Pichia pastoris is strictly induced by methanol but repressed by glycerol with an unclear molecular mechanism. In the present study, the gene of a previously characterized transmembrane protein glycerol transporter 1 (GT1) of P. pastoris GS115 was deleted by homologous recombination. Transcriptional profiles of the mutant (gt1Δ) and wild type (WT) were compared with different carbon sources (glycerol, methanol and glycerol-methanol mix) at various time points using high-throughput RNA-Seq techniques. We determined that the loss of glycerol transporter 1 (Gt1p) could relieve catabolite repression in the glycerol-methanol mixed medium and shared a similar transcriptional profile with the WT in methanol medium. By calculating the common differentially expressed genes in three distinct paired groups, genes involved in the stress response, nutrition deprivation and translational process were identified, explaining the potential roles of glycerol in the regulation of methanol metabolism. Based on weighted gene co-expression network analysis, the relationship between biological traits and the transcriptional profile was established. With the support of published research and our data, we propose two possible regulatory pathways that are involved in the regulation of catabolite repression (adenosine 5΄-monophosphate (AMP)-activated protein kinase /SNF1 and Mitogen-activated protein kinase/HOG), thereby providing potential targets for both research and industrial strain improvement.

Transcription factor Mxr1 promotes the expression of Aox1 by repressing glycerol transporter 1 in Pichia pastoris.

In the methylotrophic yeast Pichia pastoris (P. pastoris), the efficient promoter of alcohol oxidase (PAox1) is induced by methanol and repressed by glycerol, but the molecular mechanism is not clear. In this study, the relationship between alcohol oxidase 1 (aox1), methanol expression regulator 1 (mxr1) and glycerol transporter 1 (gt1) was studied. By RT-PCR, it was found that the overexpression of gt1 could increase the glycerol content in cells and repress the expression of mxr1 and aox1, and the deletion of gt1 reduced the glycerol content in cells and promoted the expression of aox1. The overexpression of mxr1 could repress the expression of gt1, and the deletion of mxr1 could promote the expression of gt1 to some extent. By EMSA, Mxr1 binding sites were found in the promoter of gt1 (PGt1) (-141 to -138, CCCC), and Mxr1 could regulate the expression of gt1 by binding to PGt1. The relationships among aox1, mxr1 and gt1 revealed here provide a reference for the understanding of the mechanism of glycerol repression of PAox1.

Identification of a novel prognostic cuproptosis-associated LncRNA signature for predicting prognosis and immunotherapy response in patients with esophageal cancer.

Nowadays, effective prognostic models for esophageal cancer (ESCA) are still lacking. Long noncoding RNAs (lncRNAs) are commonly utilized as indicators for diagnosing cancer and forecasting patient outcomes. Cuproptosis is regulated by multiple genes and is crucial to the progression of ESCA. However, it is not yet clear what role the cuproptosis-associated lncRNAs (CuALs) play in ESCA. To tackle this problem, a prognostic signature incorporating three CuALs was created. This signature was constructed by the use of the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Subsequently, the signature effectively stratified ESCA samples into a high-risk group and a low-risk group. Those in the low-risk group demonstrated extended overall survival (OS), as well as increased infiltration of T cells, macrophages, and NK cells, suggesting a potentially enhanced response to immunotherapy. The ROC curve analysis demonstrated that this prognostic signature outperformed conventional clinical factors in predicting patient prognosis (AUC = 0.708). K-M survival analysis and correlation analysis identified UGDH-AS1 (a CuAL) as a protective factor positively associated with patient prognosis. The results of RT-qPCR and wound healing assays indicated that UGDH-AS1 is overexpressed in ESCA and could inhibit cancer cell migration. In general, the prognostic signature of CuALs demonstrated a robust capability in forecasting the immune environment and patient prognosis, highlighting its potential as a tool for enhancing personalized treatment strategies in ESCA.