Cytoplasmic male sterility (CMS) arises from the incompatibility between the nucleus and cytoplasm as typical representatives of the chimeric structures in the mitochondrial genome (mitogenome), which has been extensively applied for hybrid seed production in various crops. The frequent occurrence of chimeric mitochondrial genes leading to CMS is consistent with the mitochondrial DNA (mtDNA) evolution. The sequence conservation resulting from faithfully maternal inheritance and the chimeric structure caused by frequent sequence recombination have been defined as two major features of the mitogenome. However, when and how these chimeric mitochondrial genes appear in the context of the highly conserved reproduction of mitochondria is an enigma. This review, therefore, presents the critical view of the research on CMS in plants to elucidate the mechanisms of this phenomenon. Generally, distant hybridization is the main mechanism to generate an original CMS source in natural populations and in breeding. Mitochondria and mitogenomes show pleomorphic and dynamic changes at key stages of the life cycle. The promitochondria in dry seeds develop into fully functioning mitochondria during seed imbibition, followed by massive mitochondria or mitogenome fusion and fission in the germination stage along with changes in the mtDNA structure and quantity. The mitogenome stability is controlled by nuclear loci, such as the nuclear gene Msh1. Its suppression leads to the rearrangement of mtDNA and the production of heritable CMS genes. An abundant recombination of mtDNA is also often found in distant hybrids and somatic/cybrid hybrids. Since mtDNA recombination is ubiquitous in distant hybridization, we put forward a hypothesis that the original CMS genes originated from mtDNA recombination during the germination of the hybrid seeds produced from distant hybridizations to solve the nucleo-cytoplasmic incompatibility resulting from the allogenic nuclear genome during seed germination.

UNASSIGNED: Sepsis represents a severe manifestation of infection often accompanied by metabolic disorders and mitochondrial dysfunction. Notably, mitochondrial DNA copy number (mtDNA-CN) and the expression of specific mitochondrial genes have emerged as sensitive indicators of mitochondrial function. To investigate the utility of mitochondrial gene expression in peripheral blood cells for distinguishing severe infections and predicting associated outcomes, we conducted a prospective cohort study.
UNASSIGNED: We established a prospective cohort comprising 74 patients with non-sepsis pneumonia and 67 cases of sepsis induced by respiratory infections, aging from 2 to 6 years old. We documented corresponding clinical data and laboratory information and collected blood samples upon initial hospital admission. Peripheral blood cells were promptly isolated, and both total DNA and RNA were extracted. We utilized absolute quantification PCR to assess mtDNA-CN, as well as the expression levels of mt-CO1, mt-ND1, and mt-ATP6. Subsequently, we extended these comparisons to include survivors and non-survivors among patients with sepsis using univariate and multivariate analyses. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic potential.
UNASSIGNED: The mtDNA-CN in peripheral blood cells was significantly lower in the sepsis group. Univariate analysis revealed a significant reduction in the expression of mt-CO1, mt-ND1, and mt-ATP6 in patients with sepsis. However, multivariate analysis did not support the use of mitochondrial function in peripheral blood cells for sepsis diagnosis. In the comparison between pediatric sepsis survivors and non-survivors, univariate analysis indicated a substantial reduction in the expression of mt-CO1, mt-ND1, and mt-ATP6 among non-survivors. Notably, total bilirubin (TB), mt-CO1, mt-ND1, and mt-ATP6 levels were identified as independent risk factors for sepsis-induced mortality. ROC curves were then established for these independent risk factors, revealing areas under the curve (AUCs) of 0.753 for TB (95% CI 0.596-0.910), 0.870 for mt-CO1 (95% CI 0.775-0.965), 0.987 for mt-ND1 (95% CI 0.964-1.000), and 0.877 for mt-ATP6 (95% CI 0.793-0.962).
UNASSIGNED: MtDNA-CN and mitochondrial gene expression are closely linked to the severity and clinical outcomes of infectious diseases. Severe infections lead to impaired mitochondrial function in peripheral blood cells. Notably, when compared to other laboratory parameters, the expression levels of mt-CO1, mt-ND1, and mt-ATP6 demonstrate promising potential for assessing the prognosis of pediatric sepsis.

BACKGROUND: The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition.
METHODS: Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria.
RESULTS: The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice.
CONCLUSIONS: The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.

Mitochondrial dysfunction and necrotic apoptosis, pivotal in therapeutic strategies for multiple diseases, lack comprehensive understanding in the context of renal clear cell carcinoma (ccRCC). This study explores their potential as valuable tools for ccRCC prediction, prevention, and personalized medical care. Transcriptomic and clinical datasets were acquired from the Cancer Genome Atlas (TCGA) repository. Mitochondrial and necrosis-associated gene sets were sourced from MitoCarta3.0 and the KEGG Pathway databases, respectively. Six necrosis-related mitochondrial genes (nc-MTGs) with prognostic significance were analyzed and screened, and a prognostic model was constructed. The accuracy of the model was verified using external data (E-MTAB-1980). TISCH was used to explore nc-MTGs at the cellular level. Finally, the expression level of BH3 interacting domain death agonist (BID) in ccRCC cell line was detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), and the effect of BID down-regulation on tumor cell migration was verified by transwell assays and wound-healing experiments. We established and validated a prognostic model for clear cell renal cell carcinoma (ccRCC) utilizing six necrosis-related mitochondrial genes (nc-MTGs), affirming its efficacy in evaluating tumor progression. RT-PCR results showed that BID expression was up-regulated in ccRCC tissues compared with controls and exhibited oncogenic effects. In vitro cell function experiments showed that BID may be an important factor affecting the migration of ccRCC. Our study is the first to elucidate the biological functions and prognostic significance of mitochondrial molecules related to necroptosis, providing a new way to evaluate mitochondrial therapeutics in patients with ccRCC.

BACKGROUND: Mitochondrial (MT) dysfunction is a hallmark of liver diseases. However, the effects of functional variants such as protein truncating variants (PTVs) in MT-related genes on the risk of liver diseases have not been extensively explored.
METHODS: We extracted 60,928 PTVs across 2466 MT-related nucleus genes using whole-exome sequencing data obtained from 442,603 participants in the UK Biobank. We examined their associations with liver dysfunction that represented by the liver-related biomarkers and the risks of chronic liver diseases and liver-related mortality.
RESULTS: 96.10% of the total participants carried at least one PTV. We identified 866 PTVs that were positively associated with liver dysfunction at the threshold of P value < 8.21e - 07. The coding genes of these PTVs were mainly enriched in pathways related to lipid, fatty acid, amino acid, and carbohydrate metabolisms. The 866 PTVs were presented in 1.07% (4721) of participants. Compared with participants who did not carry any of the PTVs, the carriers had a 5.33-fold (95% CI 4.15-6.85), 2.82-fold (1.69-4.72), and 4.41-fold (3.04-6.41) increased risk for fibrosis and cirrhosis of liver, liver cancer, and liver disease-related mortality, respectively. These adverse effects were consistent across subgroups based on age, sex, body mass index, smoking status, and presence of hypertension, diabetes, dyslipidemia, and metabolic syndrome.
CONCLUSIONS: Our findings revealed a significant impact of PTVs in MT-related genes on liver disease risk, highlighting the importance of these variants in identifying populations at risk of liver diseases and facilitating early clinical interventions.

Physella acuta is a freshwater snail native to North America. Understanding the phylogeography and genetic structure of P. acuta will help elucidate its evolution. In this study, we used mitochondrial (COI and 16S rDNA) and nuclear (ITS1) markers to identify the species and examine its genetic diversity, population structure, and demographic history of P. acuta in Thailand. Phylogenetic and network analyses of P. acuta in Thailand pertained to clade A, which exhibits a global distribution. Analysis of the genetic structure of the population revealed that the majority of pairwise comparisons showed no genetic dissimilarity. An isolation-by-distance test indicates no significant correlation between genetic and geographical distances among P. acuta populations, suggesting that gene flow is not restricted by distance. Demographic history and haplotype network analyses suggest a population expansion of P. acuta, as evidenced by the star-like structure detected in the median-joining network. Based on these results, we concluded that P. acuta in Thailand showed gene flow and recent population expansion. Our findings provide fundamental insights into the genetic variation of P. acuta in Thailand.

Locomotor preferences and habitat types may drive animal evolution. In this study, we speculated that locomotor preference and habitat type may have diverse influences on Bovidae mitochondrial genes. We used selection pressure and statistical analysis to explore the evolution of mitochondrial DNA (mtDNA) protein-coding genes (PCGs) from diverse locomotor preferences and habitat types. Our study demonstrates that locomotor preference (energy demand) drives the evolution of Bovidae in mtDNA PCGs. The habitat types had no significant effect on the rate of evolution in Bovidae mitochondrial genes. Our study provides deep insight into the adaptation of Bovidae.

Background: Colon adenocarcinoma (COAD) has increasing incidence and is one of the most common malignant tumors. The mitochondria involved in cell energy metabolism, oxygen free radical generation, and cell apoptosis play important roles in tumorigenesis and progression. The relationship between mitochondrial genes and COAD remains largely unknown. Methods: COAD data including 512 samples were set out from the UCSC Xena database. The nuclear mitochondrial-related genes (NMRGs)-related risk prognostic model and prognostic nomogram were constructed, and NMRGs-related gene mutation and the immune environment were analyzed using bioinformatics methods. Then, a liver metastasis model of colorectal cancer was constructed and protein expression was detected using Western blot assay. Results: A prognostic model for COAD was constructed. Comparing the prognostic model dataset and the validation dataset showed considerable correlation in both risk grouping and prognosis. Based on the risk score (RS) model, the samples of the prognostic dataset were divided into high risk group and low risk group. Moreover, pathologic N and T stage and tumor recurrence in the two risk groups were significantly different. The four prognostic factors, including age and pathologic T stage in the nomogram survival model also showed excellent predictive performance. An optimal combination of nine differentially expressed NMRGs was finally obtained, including LARS2, PARS2, ETHE1, LRPPRC, TMEM70, AARS2, ACAD9, VARS2, and ATP8A2. The high-RS group had more inflamed immune features, including T and CD4+ memory cell activation. Besides, mitochondria-associated LRPPRC and LARS2 expression levels were increased in vivo xenograft construction and liver metastases assays. Conclusion: This study established a comprehensive prognostic model for COAD, incorporating nine genes associated with nuclear-mitochondrial functions. This model demonstrates superior predictive performance across four prognostic factors: age, pathological T stage, tumor recurrence, and overall prognosis. It is anticipated to be an effective model for enhancing the prognosis and treatment of COAD.

Numerous studies have highlighted the pivotal role of mitochondria-related genes (MRGs) in the initiation and progression of glioblastoma (GBM). However, the specific contributions of MRGs coding proteins to GBM pathology remain incompletely elucidated. The identification of prognostic MRGs in GBM holds promise for the development of personalized targeted therapies and the enhancement of patient prognosis. We combined differential expression with univariate Cox regression analysis to screen prognosis-associated MRGs in GBM. Based on the nine MRGs, the hazard ratio model was conducted using a multivariate Cox regression algorithm. SHC-related survival, pathway, and immune analyses in GBM cohorts were obtained from the Biomarker Exploration of the Solid Tumor database. The proliferation and migration of U87 cells were measured by CCK-8 and transwell assay. Apoptosis in U87 cells was evaluated using flow cytometry. Confocal microscopy was employed to measure mitochondrial reactive oxygen species (ROS) levels and morphology. The expression levels of SHC1 and other relevant proteins were examined via western blotting. We screened 15 prognosis-associated MRGs and constructed a 9 MRGs-based model. Validation of the model\'s risk score confirmed its efficacy in predicting the prognosis of patients with GBM. Furthermore, analysis revealed that SHC1, a constituent MRG of the prognostic model, was upregulated and implicated in the progression, migration, and immune infiltration of GBM. In vitro experiments elucidated that p66Shc, the longest isoform of SHC1, modulates mitochondrial ROS production and morphology, consequently promoting the proliferation and migration of U87 cells. The 9 MRGs-based prognostic model could predict the prognosis of GBM. SHC1 was upregulated and correlated with the prognosis of patients by involvement in immune infiltration. Furthermore, in vitro experiments demonstrated that p66Shc promotes U87 cell proliferation and migration by mediating mitochondrial ROS production. Thus, p66Shc may serve as a promising biomarker and therapeutic target for GBM.

OBJECTIVE: The purpose of this study was to identify and analyze the mitochondrial genes associated with sepsis patients in order to elucidate the underlying mechanism of sepsis immunity and provide new ideas for the clinical treatment of sepsis.
METHODS: The hospitalized cases of sepsis (n = 20) and systemic inflammatory response syndrome (SIRS) (n = 12) admitted to the Emergency Intensive Care Unit (EICU) of the Affiliated Hospital of Southwest Medical University from January 2019 to December 2019 were collected consecutively. RNA-seq was used to sequence the RNA (mRNA) of peripheral blood cells. Bioinformatics techniques were used to screen and identify differentially expressed RNAs, with an absolute value of fold change (FC) greater than or equal to 1.2 and a false discovery rate (FDR) less than 0.05. At the same time, mitochondrial genes were obtained from the MitoCarta 3.0 database. Differential genes were then intersected with mitochondrial genes. The resulting crossover genes were subjected to GO, KEGG, and PPI analysis. Subsequently, the GSE65682 dataset was downloaded from the GEO database for survival analysis to assess the prognostic value of core genes, and GSE67652 was downloaded for ROC curve analysis to validate the diagnostic value of core genes. Finally, the localization of core genes was clarified through 10X single-cell sequencing.
RESULTS: The crossing of 314 sepsis differential genes and 1136 mitochondrial genes yielded 28 genes. GO and KEGG analysis showed that the crossover genes were mainly involved in the mitochondrion, mitochondrial matrix, and mitochondrial inner membrane. Survival analysis screened four genes that were significantly negatively associated with the prognosis of sepsis, namely FIS1, FKBP8, GLRX5, and GUK1. A comparison of peripheral blood RNA-seq results between the sepsis group and the SIRS group showed that the expression levels of these four genes were significantly decreased in the sepsis group compared to the SIRS group. ROC curve analysis based on GSE67652 indicates these four genes\' high sensitivity and specificity for sepsis detection. Additionally, single-cell RNA sequencing found that the core genes were mainly expressed in macrophages, T cells, and B cells.
CONCLUSIONS: Mitochondria-related genes (FIS1, FKBP8, GLRX5, GUK1) were underexpressed in the sepsis group, negatively correlated with survival, and mainly distributed in immune cells. This finding may guide studying the immune-related mechanisms of sepsis. This study protocol was reviewed by the Ethics Committee of the Affiliated Hospital of Southwest Medical University (ethics number: KY2018029), the clinical trial registration number is ChiCTR1900021261, and the registration date is February 4, 2019.