Senp7 deficiency impairs lipid droplets maturation in white adipose tissues via Plin4 deSUMOylation.

Lipid metabolism is important for the maintenance of physiological homeostasis. Several members of the small ubiquitin-like modifier (SUMO)-specific protease (SENP) family have been reported as the regulators of lipid homeostasis. However, the function of Senp7 in lipid metabolism remains unclear. In this study, we generated both conventional and adipocyte-specific Senp7 KO mice to characterize the role of Senp7 in lipid metabolism homeostasis. Both Senp7-deficient mice displayed reduced white adipose tissue mass and decreased size of adipocytes. By analyzing the lipid droplet morphology, we demonstrated that the lipid droplet size was significantly smaller in Senp7-deficient adipocytes. Mechanistically, Senp7 could deSUMOylate the perilipin family protein Plin4 to promote the lipid droplet localization of Plin4. Our results reveal an important role of Senp7 in the maturation of lipid droplets via Plin4 deSUMOylation.

Utility of four machine learning approaches for identifying ulcerative colitis and Crohn's disease.

Objective: Peripheral blood routine parameters (PBRPs) are simple and easily acquired markers to identify ulcerative colitis (UC) and Crohn's disease (CD) and reveal the severity, whereas the diagnostic performance of individual PBRP is limited. We, therefore used four machine learning (ML) models to evaluate the diagnostic and predictive values of PBRPs for UC and CD. Methods: A retrospective study was conducted by collecting the PBRPs of 414 inflammatory bowel disease (IBD) patients, 423 healthy controls (HCs), and 344 non-IBD intestinal diseases (non-IBD) patients. We used approximately 70 % of the PBRPs data from both patients and HCs for training, 30 % for testing, and another group for external verification. The area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnosis and prediction performance of these four ML models. Results: Multi-layer perceptron artificial neural network model (MLP-ANN) yielded the highest diagnostic performance than the other three models in six subgroups in the training set, which is helpful for discriminating IBD and HCs, UC and CD, active CD and remissive CD, active UC and remissive UC, non-IBD and HCs, and IBD and non-IBD with the AUC of 1.00, 0.988, 0.942, 1.00, 0.986, and 0.97 in the testing set, as well as the AUC of 1.00, 1.00, 0.773, 0.904, 1.00 and 0.992 in the external validation set. Conclusion: PBRPs-based MLP-ANN model exhibited good performance in discriminating between UC and CD and revealing the disease activity; however, a larger sample size and more models need to be considered for further research.

Hotspots and trends of electrochemical biosensor technology: a bibliometric analysis from 2003 to 2023.

As a powerful tool for biological sensing, electrochemical biosensors have attracted much attention due to their ability to integrate biological recognition elements on an electrochemical interface and convert target analyte information into measurable electrochemical signals. Despite the abundance of literature published on the topic, no comprehensive surveys have been conducted to evaluate the area of electrochemical biosensors with bibliometric techniques. This paper employs VOSviewer to analyze and visualize literature from 2003 to 2023 in the Web of Science in order to gain an understanding of the development of the field of electrochemical biosensors in recent years. Co-occurrence and co-citation analysis are employed to identify research hotspots, trace evolutionary paths, and comprehend development trends in the field. Moreover, by analyzing highly cited and representative literature from different time periods, it is possible to recognize the major research hotspots and grasp the development pulse. The results of this study provide a comprehensive overview of the field of electrochemical biosensors and can be used to guide future research.

Apoptotic caspase-7 activation inhibits non-canonical pyroptosis by GSDMB cleavage.

GSDMB is associated with several inflammatory diseases, such as asthma, sepsis and colitis. GZMA is released by cytotoxic lymphocytes and cleaves GSDMB at the K244 site and to induce GSDMB N-terminus dependent pyroptosis. This cleavage of GSDMB is noncell autonomous. In this study, we demonstrated that the GSDMB-N domain (1-91 aa) was important for a novel cell-autonomous function and that GSDMB could bind caspase-4 and promote noncanonical pyroptosis. Furthermore, activated caspase-7 cleaved GSDMB at the D91 site to block GSDMB-mediated promotion of noncanonical pyroptosis during apoptosis. Mechanistically, the cleaved GSDMB-C-terminus (92-417 aa) binds to the GSDMB-N-terminus (1-91 aa) to block the function of GSDMB. During E. coli and S. Typhimurium infection, inhibition of the caspase-7/GSDMB axis resulted in more pyroptotic cells. Furthermore, in a septic mouse model, caspase-7 inhibition or deficiency in GSDMB-transgenic mice led to more severe disease phenotypes. Overall, we demonstrate that apoptotic caspase-7 activation inhibits non-canonical pyroptosis by cleaving GSDMB and provide new targets for sepsis therapy.

Blocking Caspase-1/Gsdmd and Caspase-3/-8/Gsdme pyroptotic pathways rescues silicosis in mice.

Millions of patients suffer from silicosis, but it remains an uncurable disease due to its unclear pathogenic mechanisms. Though the Nlrp3 inflammasome is involved in silicosis pathogenesis, inhibition of its classic downstream factors, Caspase-1 and Gsdmd, fails to block pyroptosis and cytokine release. To clarify the molecular mechanism of silicosis pathogenesis for new therapy, we examined samples from silicosis patients and genetic mouse models. We discovered an alternative pyroptotic pathway which requires cleavage of Gsdme by Caspases-3/8 in addition to Caspase-1/Gsdmd. Consistently, Gsdmd-/-Gsdme-/- mice showed markedly attenuated silicosis pathology, and Gsdmd-/-Gsdme-/- macrophages were resistant to silica-induced pyroptosis. Furthermore, we found that in addition to Caspase 1, Caspase-8 cleaved IL-1ß in silicosis, explaining why Caspase-1-/- mice also suffered from silicosis. Finally, we found that inhibitors of Caspase-1, -3, -8 or an FDA approved drug, dimethyl fumarate, could dramatically alleviate silicosis pathology through blocking cleavage of Gsdmd and Gsdme. This study highlights that Caspase-1/Gsdmd and Caspase-3/8/Gsdme-dependent pyroptosis is essential for the development of silicosis, implicating new potential targets and drug for silicosis treatment.

The Deficiency of SCARB2/LIMP-2 Impairs Metabolism via Disrupted mTORC1-Dependent Mitochondrial OXPHOS.

Deficiency in scavenger receptor class B, member 2 (SCARB2) is related to both Gaucher disease (GD) and Parkinson's disease (PD), which are both neurodegenerative-related diseases without cure. Although both diseases lead to weight loss, which affects the quality of life and the progress of diseases, the underlying molecular mechanism is still unclear. In this study, we found that Scarb2-/- mice showed significantly reduced lipid storage in white fat tissues (WAT) compared to WT mice on a regular chow diet. However, the phenotype is independent of heat production, activity, food intake or energy absorption. Furthermore, adipocyte differentiation and cholesterol homeostasis were unaffected. We found that the impaired lipid accumulation of Adiponectin-cre; Scarb2fl/fl mice was due to the imbalance between glycolysis and oxidative phosphorylation (OXPHOS). Mechanistically, the mechanistic target of rapamycin complex 1 (mTORC1)/ eukaryotic translation initiation factor 4E binding protein 1 (4E-BP1) pathway was down-regulated in Scarb2 deficient adipocytes, leading to impaired mitochondrial respiration and enhanced glycolysis. Altogether, we reveal the role of SCARB2 in metabolism regulation besides the nervous system, which provides a theoretical basis for weight loss treatment of patients with neurodegenerative diseases.

Dysfunction of AMPA receptor GluA3 is associated with aggressive behavior in human.

Inappropriate aggression in humans hurts the society, families and individuals. The genetic basis for aggressive behavior, however, remains largely elusive. In this study, we identified two rare missense variants in X-linked GRIA3 from male patients who showed syndromes featuring aggressive outbursts. Both G630R and E787G mutations in AMPA receptor GluA3 completely lost their ion channel functions. Furthermore, a guanine-repeat single nucleotide polymorphism (SNP, rs3216834) located in the first intron of human GRIA3 gene was found to regulate GluA3 expression with longer guanine repeats (rs3216834-10G/-11G) suppressing transcription compared to the shorter ones (-7G/-8G/-9G). Importantly, the distribution of rs3216834-10G/-11G was elevated in a male violent criminal sample from Chinese Han population. Using GluA3 knockout mice, we showed that the excitatory neurotransmission and neuronal activity in the medial prefrontal cortex (mPFC) was impaired. Expressing GluA3 back into the mPFC alleviated the aggressive behavior of GluA3 knockout mice, suggesting that the defects in mPFC explained, at least partially, the neural mechanisms underlying the aggressive behavior. Therefore, our study provides compelling evidence that dysfunction of AMPA receptor GluA3 promotes aggressive behavior.

SNP rs10420324 in the AMPA receptor auxiliary subunit TARP γ-8 regulates the susceptibility to antisocial personality disorder.

In the brain, AMPA receptors mediate fast excitatory neurotransmission, the dysfunction of which leads to neuropsychiatric disorders. Synaptic function of AMPA receptors is tightly controlled by a protein group called transmembrane AMPAR regulatory proteins (TARPs). TARP γ-8 (also known as CACNG8) preferentially expresses in the hippocampus, cortex and subcortical regions that are critical for emotion generation indicating its association with psychiatric disorders. Here, we identified rs10420324 (T/G), a SNP located in the human CACNG8 gene, regulated reporter gene expression in vitro and TARP γ-8 expression in the human brain. A guanine at the locus (rs10420324G) suppressed transcription likely through modulation of a local G-quadruplex DNA structure. Consistent with these observations, the frequency of rs10420324G was higher in patients with anti-social personality disorder (ASPD) than in controls, indicating that rs10420324G in CACNG8 is more voluntary for ASPD. We then characterized the behavior of TARP γ-8 knockout and heterozygous mice and found that consistent with ASPD patients who often exhibit impulsivity, aggression, risk taking, irresponsibility and callousness, a decreased γ-8 expression in mice displayed similar behaviors. Furthermore, we found that a decrease in TARP γ-8 expression impaired synaptic AMPAR functions in layer 2-3 pyramidal neurons of the prefrontal cortex, a brain region that inhibition leads to aggression, thus explaining, at least partially, the neuronal basis for the behavioral abnormality. Taken together, our study indicates that TARP γ-8 expression level is associated with ASPD, and that the TARP γ-8 knockout mouse is a valuable animal model for studying this psychiatric disease.

Inferring the ancestry of parents and grandparents from genetic data.

Inference of admixture proportions is a classical statistical problem in population genetics. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. In this paper we show that the distribution of admixture tract lengths in a genome contains information about the admixture proportions of the ancestors of an individual. We develop a Hidden Markov Model (HMM) framework for estimating the admixture proportions of the immediate ancestors of an individual, i.e. a type of decomposition of an individual's admixture proportions into further subsets of ancestral proportions in the ancestors. Based on a genealogical model for admixture tracts, we develop an efficient algorithm for computing the sampling probability of the genome from a single individual, as a function of the admixture proportions of the ancestors of this individual. This allows us to perform probabilistic inference of admixture proportions of ancestors only using the genome of an extant individual. We perform extensive simulations to quantify the error in the estimation of ancestral admixture proportions under various conditions. To illustrate the utility of the method, we apply it to real genetic data.

A SNP of bacterial blc disturbs gut lysophospholipid homeostasis and induces inflammation through epithelial barrier disruption.

BACKGROUND: Alteration of commensal bacterial composition is associated with many inflammatory diseases. However, few studies have pinpointed the specific bacterial genes that may suppress host immune responses against microbes and maintain homeostasis in the host intestine. METHODS: High-throughput screening was performed in Caenorhabditis elegans with a single gene knockout ut screening was performed in Caenorhabditis elegans with a single gene knockout Escherichia coli (E. coli) library and identified the immune suppression gene blc. The coding sequences of blc among different kinds of E. coli strains were aligned to identify the single nucleotide polymorphisms (SNPs). Physiological and biochemical experiments were performed in C. elegans and mice to explore the function of the blc variant. FINDINGS: By screening 3983 E. coli mutants, we discovered that 9 bacterial genes, when deleted, activate innate immunity in the host C. elegans. Among these 9 genes, the gene encoding blc showed a distinctive SNP in many clinically pathogenic bacteria. We found that bacteria with this SNP, which converts Blc G84 to Blc E84, are highly enriched in the faeces of patients with inflammatory bowel disease (IBD). Exposure to BlcE84-encoding bacteria resulted in epithelial barrier disruption and immune activation in both worms and mice. Detailed analysis indicated that infection with BlcE84-encoding bacteria causes a significant decrease in LPE levels in the intestine and subsequently disrupts gut epithelial integrity in mice. Consistently, the levels of LPE in patients with IBD are significantly lower than those in healthy people. Finally, supplementation with LPE, which activates LPA1/PLCß/PKC signaling, reversed the defects induced by BlcE84-encoding bacteria. INTERPRETATION: Our results identified a novel bacterial gene, blc, in E. coli that regulates host gut integrity and immunity. FUND: The Ministry of Science and Technology of China; the National Natural Science Foundation of China; and the Natural Science Foundation of Jiangsu Province.

Magnesium protects against sepsis by blocking gasdermin D N-terminal-induced pyroptosis.

Hypomagnesemia is a significant risk factor for critically ill patients to develop sepsis, a life-threatening disease with a mortality rate over 25%. Our clinic data analysis showed that hypomagnesemia is associated with a decreased monocyte count in septic patients. At the cellular level, we found that Mg2+ inhibits pyroptosis. Specifically, Mg2+ limits the oligomerization and membrane localization of gasdermin D N-terminal (GSDMD-NT) upon the activation of either the canonical or noncanonical pyroptotic pathway. Mechanistically, we demonstrated that Ca2+ influx is a prerequisite for the function of GSDMD-NT. Mg2+ blocks Ca2+ influx by inhibiting the ATP-gated Ca2+ channel P2X7, thereby impeding the function of GSDMD-NT and inhibiting lipopolysaccharide (LPS)-induced noncanonical pyroptosis. Furthermore, Mg2+ administration protects mice from LPS-induced lethal septic shock. Together, our data reveal the underlying mechanism of how Mg2+ inhibits pyroptosis and suggest potential clinic applications of magnesium supplementation for sepsis prevention and treatment.

An improved approach for reconstructing consensus repeats from short sequence reads.

BACKGROUND: Repeat elements are important components of most eukaryotic genomes. Most existing tools for repeat analysis rely either on high quality reference genomes or existing repeat libraries. Thus, it is still challenging to do repeat analysis for species with highly repetitive or complex genomes which often do not have good reference genomes or annotated repeat libraries. Recently we developed a computational method called REPdenovo that constructs consensus repeat sequences directly from short sequence reads, which outperforms an existing tool called RepARK. One major issue with REPdenovo is that it doesn't perform well for repeats with relatively high divergence rates or low copy numbers. In this paper, we present an improved approach for constructing consensus repeats directly from short reads. Comparing with the original REPdenovo, the improved approach uses more repeat-related k-mers and improves repeat assembly quality using a consensus-based k-mer processing method. RESULTS: We compare the performance of the new method with REPdenovo and RepARK on Human, Arabidopsis thaliana and Drosophila melanogaster short sequencing data. And the new method fully constructs more repeats in Repbase than the original REPdenovo and RepARK, especially for repeats of higher divergence rates and lower copy number. We also apply our new method on Hummingbird data which doesn't have a known repeat library, and it constructs many repeat elements that can be validated using PacBio long reads. CONCLUSION: We propose an improved method for reconstructing repeat elements directly from short sequence reads. The results show that our new method can assemble more complete repeats than REPdenovo (and also RepARK). Our new approach has been implemented as part of the REPdenovo software package, which is available for download at https://github.com/Reedwarbler/REPdenovo .

CircMarker: a fast and accurate algorithm for circular RNA detection.

BACKGROUND: While RNA is often created from linear splicing during transcription, recent studies have found that non-canonical splicing sometimes occurs. Non-canonical splicing joins 3' and 5' and forms the so-called circular RNA. It is now believed that circular RNA plays important biological roles such as affecting susceptibility of some diseases. During the past several years, multiple experimental methods have been developed to enrich circular RNA while degrade linear RNA. Although several useful software tools for circular RNA detection have been developed as well, these tools are based on reads mapping may miss many circular RNA. Also, existing tools are slow for large data due to their dependence on reads mapping. METHOD: In this paper, we present a new computational approach, named CircMarker, based on k-mers rather than reads mapping for circular RNA detection. CircMarker takes advantage of transcriptome annotation files to create the k-mer table for circular RNA detection. RESULTS: Empirical results show that CircMarker outperforms existing tools in circular RNA detection on accuracy and efficiency in many simulated and real datasets. CONCLUSIONS: We develop a new circular RNA detection method called CircMarker based on k-mer analysis. Our results on both simulation data and real data demonstrate that CircMarker runs much faster and can find more circular RNA with higher consensus-based sensitivity and high accuracy ratio compared with existing tools.

CLADES: A classification-based machine learning method for species delimitation from population genetic data.

Species are considered to be the basic unit of ecological and evolutionary studies. As multilocus genomic data are increasingly available, there have been considerable interests in the use of DNA sequence data to delimit species. In this study, we show that machine learning can be used for species delimitation. Our method treats the species delimitation problem as a classification problem for identifying the category of a new observation on the basis of training data. Extensive simulation is first conducted over a broad range of evolutionary parameters for training purposes. Each pair of known populations is combined to form training samples with a label of "same species" or "different species". We use support vector machine (SVM) to train a classifier using a set of summary statistics computed from training samples as features. The trained classifier can classify a test sample to two outcomes: "same species" or "different species". Given multilocus genomic data of multiple related organisms or populations, our method (called CLADES) performs species delimitation by first classifying pairs of populations. CLADES then delimits species by maximizing the likelihood of species assignment for multiple populations. CLADES is evaluated through extensive simulation and also tested on real genetic data. We show that CLADES is both accurate and efficient for species delimitation when compared with existing methods. CLADES can be useful especially when existing methods have difficulty in delimitation, for example with short species divergence time and gene flow.

STELLS2: fast and accurate coalescent-based maximum likelihood inference of species trees from gene tree topologies.

MOTIVATION: It is well known that gene trees and species trees may have different topologies. One explanation is incomplete lineage sorting, which is commonly modeled by the coalescent process. In multispecies coalescent, a gene tree topology is observed with some probability (called the gene tree probability) for a given species tree. Gene tree probability is the main tool for the program STELLS, which finds the maximum likelihood estimate of the species tree from the given gene tree topologies. However, STELLS becomes slow when data size increases. Recently, several fast species tree inference methods have been developed, which can handle large data. However, these methods often do not fully utilize the information in the gene trees. RESULTS: In this paper, we present an algorithm (called STELLS2) for computing the gene tree probability more efficiently than the original STELLS. The key idea of STELLS2 is taking some 'shortcuts' during the computation and computing the gene tree probability approximately. We apply the STELLS2 algorithm in the species tree inference approach in the original STELLS, which leads to a new maximum likelihood species tree inference method (also called STELLS2). Through simulation we demonstrate that the gene tree probabilities computed by STELLS2 and STELLS have strong correlation. We show that STELLS2 is almost as accurate in species tree inference as STELLS. Also STELLS2 is usually more accurate than several existing methods when there is one allele per species, although STELLS2 is slower than these methods. STELLS2 outperforms these methods significantly when there are multiple alleles per species. AVAILABILITY AND IMPLEMENTATION: The program STELLS2 is available for download at: https://github.com/yufengwudcs/STELLS2. CONTACT: yufeng.wu@uconn.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.