The global state of research in stem cells therapy for spinal cord injury (2003-2022): a visualized analysis.

Objective: Our study aimed to visualize the global status and frontiers in stem cell therapy for spinal cord injury by using bibliometric methodology. Methods: Publication citation information related to stem cell therapy for spinal cord injury (SCI) studies between 2003 and 2022 was retrieved from the Web of Science Core Collection database. For the visualized study, VOS viewer software and Graph Pad Prism 9.5 were used to perform bibliometric analysis of included data and publication number statistics in stem cell therapy for the SCI domain. Results: A total of 6,686 publications were retrieved. The USA and China made the highest contributions to global research with the highest number of citations and link strength. The journal Experimental Neurology ranks as the top journal, combining the publication amount and bibliometrics results. The University of Toronto, based in Canada, was the first-ranking institution. The directions of the current study could be divided into five clusters. The research of Transplantation and Regenerative Medicine and Neurosciences Mechanism Research may be the emerging frontiers in this domain. Conclusion: In summary, stem cell therapy for spinal cord injuries is poised for more valuable advances.

Immune Cells in the Spleen of Mice Mediate the Inflammatory Response Induced by Mannheimia haemolytica A2 Serotype.

(1) Background: Mannheimia haemolytica (M. haemolytica) is an opportunistic pathogen and is mainly associated with respiratory diseases in cattle, sheep, and goats. (2) Methods: In this study, a mouse infection model was established using a M. haemolytica strain isolated from goats. Histopathological observations were conducted on various organs of the mice, and bacterial load determination and RNA-seq analysis were specifically performed on the spleens of the mice. (3) Results: The findings of this study suggest that chemokines, potentially present in the spleen of mice following a M. haemolytica challenge, may induce the migration of leukocytes to the spleen and suppress the release of pro-inflammatory factors through a negative feedback regulation mechanism. Additionally, an interesting observation was made regarding the potential of hematopoietic stem/progenitor cells congregating in the spleen to differentiate into immune cells, which could potentially collaborate with leukocytes in their efforts to counteract M. haemolytica invasion. (4) Conclusions: This study revealed the immune regulation mechanism induced by M. haemolytica in the mouse spleen, providing valuable insights into host-pathogen interactions and offering a theoretical basis for the prevention, control, and treatment of mannheimiosis.

Phase separation as a possible mechanism for dosage sensitivity.

BACKGROUND: Deletion of haploinsufficient genes or duplication of triplosensitive ones results in phenotypic effects in a concentration-dependent manner, and the mechanisms underlying these dosage-sensitive effects remain elusive. Phase separation drives functional compartmentalization of biomolecules in a concentration-dependent manner as well, which suggests a potential link between these two processes, and warrants further systematic investigation. RESULTS: Here we provide bioinformatic and experimental evidence to show a close link between phase separation and dosage sensitivity. We first demonstrate that haploinsufficient or triplosensitive gene products exhibit a higher tendency to undergo phase separation. Assessing the well-established dosage-sensitive genes HNRNPK, PAX6, and PQBP1 with experiments, we show that these proteins undergo phase separation. Critically, pathogenic variations in dosage-sensitive genes disturb the phase separation process either through reduced protein levels, or loss of phase-separation-prone regions. Analysis of multi-omics data further demonstrates that loss-of-function genetic perturbations on phase-separating genes cause similar dysfunction phenotypes as dosage-sensitive gene perturbations. In addition, dosage-sensitive scores derived from population genetics data predict phase-separating proteins with much better performance than available sequence-based predictors, further illustrating close ties between these two parameters. CONCLUSIONS: Together, our study shows that phase separation is functionally linked to dosage sensitivity and provides novel insights for phase-separating protein prediction from the perspective of population genetics data.

Pancreatic cancer stem cell-derived exosomal miR-210 mediates macrophage M2 polarization and promotes gemcitabine resistance by targeting FGFRL1.

Pancreatic cancer (PC) is a serious threat to human health, with most patients diagnosed at the advanced stages of the disease. Treatment with gemcitabine (GEM) leads to PC GEM resistance. In addition, cancer stem cell (CSC)-derived exosomes play an important role in cancer progression. We aimed to investigate the role and mechanism of action of PC stem cell-derived exosomes in PC drug resistance and progression. CSC-derived exosomes increased the proportion of F4/80+/CD86 + cells and levels of M2 polarization factors. miR-210 is expressed in CSC-derived exosomes. Thus, following co-culture, miR-210 was taken up by macrophages. Transfection or the addition of miR-210 mimics increased the proportion of F4/80+/CD206 + cells and levels of M2 polarization factors. Further, the miR-210 targets inhibited the levels of FGFRL1. The FGFRL1 overexpression plasmid also inhibited miR-210-mediated M2 polarization. After co-culture of THP-M2 cells with PC cells and treatment with GEM, the survival rate, migration rate, and levels of MDR, YB-1, BCRP, p-PI3K, p-AKT, and p-mTOR in PC cells increased. And THP-M2 increased the tumor volume and MDR, YB-1, BCRP, p-PI3K, p-AKT, and p-mTOR levels. Overall, miR-210 from PC stem cell-derived exosome targets and inhibits FGFRL1 to promote macrophage M2 polarization, which activates the p-PI3K/p-AKT/p-mTOR pathway and increases GEM resistance.

VIPpred: a novel model for predicting variant impact on phosphorylation events driving carcinogenesis.

Disrupted protein phosphorylation due to genetic variation is a widespread phenomenon that triggers oncogenic transformation of healthy cells. However, few relevant phosphorylation disruption events have been verified due to limited biological experimental methods. Because of the lack of reliable benchmark datasets, current bioinformatics methods primarily use sequence-based traits to study variant impact on phosphorylation (VIP). Here, we increased the number of experimentally supported VIP events from less than 30 to 740 by manually curating and reanalyzing multi-omics data from 916 patients provided by the Clinical Proteomic Tumor Analysis Consortium. To predict VIP events in cancer cells, we developed VIPpred, a machine learning method characterized by multidimensional features that exhibits robust performance across different cancer types. Our method provided a pan-cancer landscape of VIP events, which are enriched in cancer-related pathways and cancer driver genes. We found that variant-induced increases in phosphorylation events tend to inhibit the protein degradation of oncogenes and promote tumor suppressor protein degradation. Our work provides new insights into phosphorylation-related cancer biology as well as novel avenues for precision therapy.

MST2 methylation by PRMT5 inhibits Hippo signaling and promotes pancreatic cancer progression.

The Hippo signaling axis is a tumor suppressor pathway that is activated by various extra-pathway factors to regulate cell differentiation and organ development. Recent studies have reported that autophosphorylation of the core kinase cassette stimulates activation of the Hippo signaling cascade. Here, we demonstrate that protein arginine methyltransferase 5 (PRMT5) contributes to inactivation of the Hippo signaling pathway in pancreatic cancer. We show that the Hippo pathway initiator serine/threonine kinase 3 (STK3, also known as MST2) of Hippo signaling pathway can be symmetrically di-methylated by PRMT5 at arginine-461 (R461) and arginine-467 (R467) in its SARAH domain. Methylation suppresses MST2 autophosphorylation and kinase activity by blocking its homodimerization, thereby inactivating Hippo signaling pathway in pancreatic cancer. Moreover, we also show that the specific PRMT5 inhibitor GSK3326595 re-activates the dysregulated Hippo signaling pathway and inhibits the growth of human pancreatic cancer xenografts in immunodeficient mice, thus suggesting potential clinical application of PRMT5 inhibitors in pancreatic cancer.

Investigating phase separation properties of chromatin-associated proteins using gradient elution of 1,6-hexanediol.

BACKGROUND: Chromatin-associated phase separation proteins establish various biomolecular condensates via liquid-liquid phase separation (LLPS), which regulates vital biological processes spatially and temporally. However, the widely used methods to characterize phase separation proteins are still based on low-throughput experiments, which consume time and could not be used to explore protein LLPS properties in bulk. RESULTS: By combining gradient 1,6-hexanediol (1,6-HD) elution and quantitative proteomics, we developed chromatin enriching hexanediol separation coupled with liquid chromatography-mass spectrometry (CHS-MS) to explore the LLPS properties of different chromatin-associated proteins (CAPs). First, we found that CAPs were enriched more effectively in the 1,6-HD treatment group than in the isotonic solution treatment group. Further analysis showed that the 1,6-HD treatment group could effectively enrich CAPs prone to LLPS. Finally, we compared the representative proteins eluted by different gradients of 1,6-HD and found that the representative proteins of the 2% 1,6-HD treatment group had the highest percentage of IDRs and LCDs, whereas the 10% 1,6-HD treatment group had the opposite trend. CONCLUSION: This study provides a convenient high-throughput experimental method called CHS-MS. This method can efficiently enrich proteins prone to LLPS and can be extended to explore LLPS properties of CAPs in different biological systems.

Epidemiological characteristics of SHV, cmlv, and FosA6-producing carbapenem-resistant Klebsiella pneumoniae based on whole genome sequences in Jiangsu, China.

Carbapenem-resistant Klebsiella pneumoniae (CRKP), particularly those with high virulence, cause invasive disease in clinical settings. An epidemiological investigation was conducted on the evolution, virulence, and antimicrobial resistance of CRKP isolates in two tertiary teaching hospitals in Jiangsu, China from November 2020 to December 2021. There were 31 different CRKP strains discovered. We performed whole genome sequencing (WGS) on 13 SHV, cmlv, and FosA6-producing CRKP to reveal molecular characteristics. Five ST15/ST11 isolates had CRISPR-Cas systems. By conjugation tests, KPC-2 can be transmitted horizontally to E. coil. A conjugative pHN7A8-related multi-resistance plasmid (KPC-2, blaCTX-M-65, blaTEM-1, fosA3, catII, and rmtB) was first discovered in CRKP clinical isolates. Using bacteriological testing, a serum killing assay, and an infection model with Galleria mellonella, three ST11-K64 KPC-2 generating carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKP) were identified. These strains harbored a virulent plasmid and an IncFII-family pKPC/pHN7A8 conjugative plasmid, which led to hypervirulence and resistance. One of these CR-hvKPs, which co-harbored KPC-2, NDM-6, SHV-182, SHV-64, and blaCTX-M-122 genes, was first discovered. Importantly, this CR-hvKP strain also produced biofilm and had non-inferior fitness. The widespread use of ceftazidime/avibactam might provide this CR-hvKP with a selective advantage; hence, immediate action is required to stop its dissemination. Another important finding is the novel ST6136 in K. pneumoniae. Finally, the sterilization efficiency rates of Fe2C nanoparticles in CRKP were more than 98%. Furthermore, our novel antibacterial Fe2C nanoparticles may also provide a therapeutic strategy for infections.

Development and Experimental Validation of a Novel Prognostic Signature for Gastric Cancer.

BACKGROUND: Gastric cancer is a malignant tumor with high morbidity and mortality. Therefore, the accurate recognition of prognostic molecular markers is the key to improving treatment efficacy and prognosis. METHODS: In this study, we developed a stable and robust signature through a series of processes using machine-learning approaches. This PRGS was further experimentally validated in clinical samples and a gastric cancer cell line. RESULTS: The PRGS is an independent risk factor for overall survival that performs reliably and has a robust utility. Notably, PRGS proteins promote cancer cell proliferation by regulating the cell cycle. Besides, the high-risk group displayed a lower tumor purity, higher immune cell infiltration, and lower oncogenic mutation than the low-PRGS group. CONCLUSIONS: This PRGS could be a powerful and robust tool to improve clinical outcomes for individual gastric cancer patients.

Sequence determinants and solution conditions underlying liquid to solid phase transition.

Life consists of numberless functional biomolecules that exist in various states. Besides well-dissolved phases, biomolecules especially proteins and nucleic acids can form liquid droplets through liquid-liquid phase separation (LLPS). Stronger interactions promote a solid-like state of biomolecular condensates, which are also formerly referred to as detergent-insoluble aggregates. Solid-like condensates exist in vivo physiologically and pathologically, and their formation has not been fully understood. Recently, more and more research has proven that liquid to solid phase transition (LST) is an essential way to form solid condensates. In this review, we summarized the regions in the sequence that have different impacts on phase transition and emphasized that the LST is affected by its sequence characteristics. Moreover, increasing evidence unveiled that LST is affected by various solution conditions. We discussed solution conditions like protein concentration, pH, ATP, ions, and small molecules in a solution. Methods have been established to study these solid phase components. Here, we summarized low-throughput experimental techniques and high-throughput omics methods in the study of the LST.

PhaSepDB in 2022: annotating phase separation-related proteins with droplet states, co-phase separation partners and other experimental information.

Phase separation (PS) proteins form droplets to regulate myriad membraneless organelles (MLOs) and cellular pathways such as transcription, signaling transduction and protein degeneration. PS droplets are usually liquid-like and can convert to hydrogel/solid-like under certain conditions. The PS behavior of proteins is regulated by co-PS partners and mutations, modifications, oligomerizations, repeat regions and alternative splicing of the proteins. With growing interest in PS condensates and associated proteins, we established PhaSepDB 1.0, which provided experimentally verified PS proteins and MLO-related proteins. The past few years witnessed a surge in PS-related research works; thus, we kept updating PhaSepDB. The current PhaSepDB contains 1419 PS entries, 770 low-throughput MLO-related entries and 7303 high-throughput MLO-related entries. We provided more detailed annotations of PS proteins, including PS verification experiments, regions used in experiments, phase diagrams of different experimental conditions, droplet states, co-PS partners and PS regulatory information. We believe that researchers can go further in studying PS proteins with the updated PhaSepDB (http://db.phasep.pro/).

Sheep and goat pathogen database: a pathogen data integration and analysis database of sheep and goat infectious diseases.

The prevalence of infectious diseases in sheep and goats has a significant impact on the development of the sheep and goat industry and public health security. The identification and analysis of pathogens are crucial for infectious disease research; however, existing databases pay little attention to sheep and goat diseases, and pathogen data are relatively scattered. Therefore, the effective integration, analysis and visualization of these data will help us conduct in-depth research on sheep and goat infectious diseases and promote the formulation of disease prevention and control strategies. This article considered the pathogens of 44 infectious diseases in sheep and goats as the main research objects and collected and downloaded relevant scientific literature, pathogen genomes, pathogen transcriptomes, pathogen occurrence records, and other data. The C# programming language and an SQL Server database were used to construct and realize the functions of the Sheep and Goat Pathogen Database (SGPD) within a B/S architecture based on the ASP.NET platform. The SGPD mainly provides an integrated platform for sheep and goat pathogen data retrieval, auxiliary analysis, and user upload, including several functionalities: (1) a Disease Introduction module that queries basic information regarding the 44 recorded sheep and goat infectious diseases, such as epidemiology, clinical characteristics, diagnostic criteria, and prevention and control measures; (2) an Omics Information module that allows users to query and download the genome and transcriptome data related to the pathogens of sheep and goat infectious disease, and provide sequence alignment functionality; (3) a Pathogen Structure module that enables users to view electron micrographs of pathogen structure and tissue sections related to sheep and goat disease from publicly published research; (4) a Literature Search module based on the "Pathogen Dictionary" search strategy that facilitates searches for published research related to pathogens of infectious disease; (5) a Science Popularization module that allows users to view popular science materials related to sheep and goat infectious diseases; and (6) a Public Health module that allows users to query the risk factors of zoonotic disease transmission and the corresponding related literature, and realize the visualization of pathogen distribution. The SGPD is a specialized sheep and goat pathogen information database that provides comprehensive resources and technical support for sheep and goat infectious disease research, prevention, and control.

Tumor Cell Derived Exosomal GOT1 Suppresses Tumor Cell Ferroptosis to Accelerate Pancreatic Cancer Progression by Activating Nrf2/HO-1 Axis via Upregulating CCR2 Expression.

Recently, evidence has shown that GOT1 expression is upregulated in pancreatic cancer tissues and promotes cancer development, but the specific mechanism remains unclear. We found that GOT1 expression was upregulated in pancreatic cancer cell-derived exosomes. When PANC-1 cells were incubated with exosomes alone or transfected together with si-GOT1, we found that exosomes enhanced cell proliferation, invasion and migration, promoted ferroptosis, and si-GOT1 reversed the effects of exosomes. The results of online bioinformatics database analysis indicated that CCR2 was a potential binding protein of GOT1 and is highly expressed in pancreatic cancer tissues. PANC-1 cells were transfected with pcDNA-CCR2 or si-CCR2, and it was found that pcDNA-CCR2 enhanced cell proliferation, invasion and migration, promoted ferroptosis, and si-CCR2 had an opposite effect. Next, exosome-treated cells were transfected with si-GOT1 alone or together with pcDNA-CCR2, and we found that exosomes promoted CCR2 expression, promoted cell proliferation and invasion, and inhibited ferroptosis, the transfection of si-GOT1 abolished the effect of exosomes, and the transfection of pcDNA-CCR2 again reversed the effect of si-GOT1. Furthermore, when exosome-treated cells were transfected with si-GOT1 alone or co-incubated with Nrf2 activator NK-252, we found that si-GOT1 reversed the promoting effect of exosomes on Nrf2 and HO-1 expression, as well as its inhibitory effect on ferroptosis, but this effect was abrogated by NK-252. In vivo studies showed that knockdown of GOT1 expression inhibited tumor formation compared with tumor tissues formed upon exosome induction, which was mediated by promoting ferroptosis via suppressing the protein expression of GOT1, CCR2, Nrf2 and HO-1 in tumor tissues.

Identification of CKS2 and RRM2 as potential markers of vitiligo using bioinformatics analysis.

Previous studies have attempted to elucidate the molecular mechanism of vitiligo; however, its pathogenesis remains unclear. This study aimed to explore biomarkers related to vitiligo through bioinformatic analysis. The microarray datasets GSE53146 and GSE65127 were downloaded from the Gene Expression Omnibus database. Firstly, differentially expressed genes (DEGs) in GSE53146 were screened, and then an enrichment analysis was performed. Secondly, the protein-protein interaction (PPI) network of DEGs was constructed using the STRING database, and the key genes were screened using the MCODE plugin in Cytoscape and verified using GSE65127. Finally, quantiseq was used to evaluate immune cell infiltration in vitiligo, then to observe the correlation between biomarkers and immune cells. In total, 544 DEGs were identified, including 342 upregulated and 202 downregulated genes. Gene Ontology (GO) enrichment showed that DEGs were related to inflammatory and immune responses, and Kyoto Encyclopedia of Genes and Genomes enrichment showed that DEGs were involved in many autoimmune diseases. In the PPI network, 7 key genes, CENPN, CKS2, PLK4, RRM2, TPX2, CCNA2, and CDC45 were identified by MCODE cluster and verified using the GSE65127 dataset. With an area under the curve (AUC) > 0.8 as the standard, 2 genes were screened, namely CKS2 and RRM2. Further immune infiltration analysis showed that M2 macrophages were involved in the pathogenesis of vitiligo, whereas CKS2 and RRM2 were both related to M2 macrophages. This study shows that CKS2 and RRM2 have potential as biomarkers of vitiligo and provides a theoretical basis for a better understanding of the pathogenesis of vitiligo.

Screening membraneless organelle participants with machine-learning models that integrate multimodal features.

Protein self-assembly is one of the formation mechanisms of biomolecular condensates. However, most phase-separating systems (PS) demand multiple partners in biological conditions. In this study, we divided PS proteins into two groups according to the mechanism by which they undergo PS: PS-Self proteins can self-assemble spontaneously to form droplets, while PS-Part proteins interact with partners to undergo PS. Analysis of the amino acid composition revealed differences in the sequence pattern between the two protein groups. Existing PS predictors, when evaluated on two test protein sets, preferentially predicted self-assembling proteins. Thus, a comprehensive predictor is required. Herein, we propose that properties other than sequence composition can provide crucial information in screening PS proteins. By incorporating phosphorylation frequencies and immunofluorescence image-based droplet-forming propensity with other PS-related features, we built two independent machine-learning models to separately predict the two protein categories. Results of independent testing suggested the superiority of integrating multimodal features. We performed experimental verification on the top-scored proteins DHX9, Ki-67, and NIFK. Their PS behavior in vitro revealed the effectiveness of our models in PS prediction. Further validation on the proteome of membraneless organelles confirmed the ability of our models to identify PS-Part proteins. We implemented a web server named PhaSePred (http://predict.phasep.pro/) that incorporates our two models together with representative PS predictors. PhaSePred displays proteome-level quantiles of different features, thus profiling PS propensity and providing crucial information for identification of candidate proteins.

HDAC5 modulates PD-L1 expression and cancer immunity via p65 deacetylation in pancreatic cancer.

Rationale: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with a dismal 5-year survival less than 10%. Most patients with PDAC exhibit poor response to single-agent immunotherapy. Multimodal therapies targeting mechanisms of resistance to immunotherapy are urgently needed. We found that the class IIa histone deacetylase (HDAC) member, HDAC5 is downregulated in multiple solid tumors and its level were associated with favorable prognosis in PDAC patients. Upregulated genes in patients harboring HDAC5 deletions were enriched in adaptive immune responses and lymphocyte-mediated immunity in The Cancer Genome Atlas (TCGA) pancreatic cancer dataset. Methods: Tissue microarray of pancreatic cancer were used to analysis the correlation between HDAC5 and PD-L1. RNA-seq, transcription factor motif analysis, drug screening and molecular biology assays were performed to identify the mechanism of HDAC5's repression on PD-L1. Allografts of pancreatic cancer in mouse were applied to test the efficiency of HDAC5 inhibition and anti-PD1 co-treatment. Results: HDAC5 regulated PD-L1 expression by directly interacting with NF-κB p65; this interaction was suppressed by p65 phosphorylation at serine-311. Additionally, HDAC5 diminished p65 acetylation at lysine-310, which is essential for the transcriptional activity of p65. Importantly, we demonstrated that HDAC5 silencing or inhibition sensitized PDAC tumors to immune checkpoint blockade (ICB) therapy in syngeneic mouse model and KPC mouse derived PDAC model. Conclusion: Our findings revealed a previously unknown role of HDAC5 in regulating the NF-κB signaling pathway and antitumor immune responses. These findings provide a strong rationale for augment the antitumor effects of ICB in immunotherapy-resistant PDAC by inhibiting HDAC5.

Quantifying the phase separation property of chromatin-associated proteins under physiological conditions using an anti-1,6-hexanediol index.

BACKGROUND: Liquid-liquid phase separation (LLPS) is an important organizing principle for biomolecular condensation and chromosome compartmentalization. However, while many proteins have been reported to undergo LLPS, quantitative and global analysis of chromatin LLPS property remains absent. RESULTS: Here, by combining chromatin-associated protein pull-down, quantitative proteomics and 1,6-hexanediol (1,6-HD) treatment, we develop Hi-MS and define an anti-1,6-HD index of chromatin-associated proteins (AICAP) to quantify 1,6-HD sensitivity of chromatin-associated proteins under physiological conditions. Compared with known physicochemical properties involved in phase separation, we find that proteins with lower AICAP are associated with higher content of disordered regions, higher hydrophobic residue preference, higher mobility and higher predicted LLPS potential. We also construct BL-Hi-C libraries following 1,6-HD treatment to study the sensitivity of chromatin conformation to 1,6-HD treatment. We find that the active chromatin and high-order structures, as well as the proteins enriched in corresponding regions, are more sensitive to 1,6-HD treatment. CONCLUSIONS: Our work provides a global quantitative measurement of LLPS properties of chromatin-associated proteins and higher-order chromatin structure. Hi-MS and AICAP data provide an experimental tool and quantitative resources valuable for future studies of biomolecular condensates.

Correction: Insulin resistance enhances the mitogen-activated protein kinase signaling pathway in ovarian granulosa cells.

[This corrects the article DOI: 10.1371/journal.pone.0188029.].

Computational Screening of Phase-separating Proteins.

Phase separation is an important mechanism that mediates the compartmentalization of proteins in cells. Proteins that can undergo phase separation in cells share certain typical sequence features, like intrinsically disordered regions (IDRs) and multiple modular domains. Sequence-based analysis tools are commonly used in the screening of these proteins. However, current phase separation predictors are mostly designed for IDR-containing proteins, thus inevitably overlook the phase-separating proteins with relatively low IDR content. Features other than amino acid sequence could provide crucial information for identifying possible phase-separating proteins: protein-protein interaction (PPI) networks show multivalent interactions that underlie phase separation process; post-translational modifications (PTMs) are crucial in the regulation of phase separation behavior; spherical structures revealed in immunofluorescence (IF)images indicate condensed droplets formed by phase-separating proteins, distinguishing these proteins from non-phase-separating proteins. Here, we summarize the sequence-based tools for predicting phase-separating proteins and highlight the importance of incorporating PPIs, PTMs, and IF images into phase separation prediction in future studies.