Short cell-penetration peptide conjugated bioreducible polymer enhances gene editing of CRISPR system.

CRISPR-based gene therapy offers precise targeting and specific editing of disease-related gene sequences, potentially yielding long-lasting treatment effects. However, efficient delivery remains a significant challenge for its widespread application. In this study, we design a novel short peptide-conjugated bioreducible polymer named TSPscp as a safe and effective delivery vector for the CRISPR system. Our results show that TSPscp markedly boosts transcriptional activation and genome editing activities of multiple CRISPR systems as confirmed by decomposition-seq and Deep-seq, which is resulted from its capability in facilitating delivery of plasmid DNA by promoting cellular uptake and lysosomal escape. Additionally, TSPscp further enhances genome editing of CRISPR by delivery of minicircle DNA, a condensed form of regular plasmid DNA. More importantly, TSPscp significantly improves delivery and genome editing of CRISPR system in vivo. In summary, our study highlights TSPscp as a promising delivery tool for CRISPR applications in vivo.

The m6 A modification of Il17a in CD4+ T cells promotes inflammation in psoriasis.

Psoriasis is a chronic inflammatory skin disorder. The mechanism of psoriasis pathogenesis is not entirely clear. Here, we reported that the level of the N6-methyladenosine (m6 A) modification was increased in psoriatic CD4+ T cells compared with healthy controls. In the psoriasis mouse model, depletion of the RNA demethylase, Alkbh5, from CD4+ T cells promoted the psoriasis-like phenotype and inflammation. Intriguingly, this phenotype and inflammation were alleviated by the ablation of the m6 A methyltransferase Mettl3 in CD4+ T cells. Mechanistically, we found that the m6 A modification of IL17A mRNA increased the expression of IL-17A (an important pro-inflammatory factor in psoriasis) and promoted psoriasis. Thus, our study provided evidence that the m6 A modification of IL17A in CD4+ T cells regulates inflammation in psoriasis.

SLC35E1 promotes keratinocyte proliferation in psoriasis by regulating zinc homeostasis.

Keratinocyte hyperproliferation is a key pathogenic factor in psoriasis. However, the mechanisms that regulate keratinocyte hyperproliferation in this condition remain unclear. Here, we found that SLC35E1 was highly expressed in keratinocytes of patients with psoriasis and that Slc35e1-/- mice displayed a less severe imiquimod (IMQ)-induced psoriasis-like phenotype than their wild-type siblings. In addition, SLC35E1 deficiency inhibited keratinocyte proliferation in both mice and cultured cells. On a molecular level, SLC35E1 was found to regulate zinc ion concentrations and subcellular localization, while zinc ion chelation reversed the IMQ-induced psoriatic phenotype in Slc35e1-/- mice. Meanwhile, epidermal zinc ion levels were decreased in patients with psoriasis and zinc ion supplementation alleviated the psoriatic phenotype in an IMQ-induced mouse model of psoriasis. Our results indicated that SLC35E1 can promote keratinocyte proliferation by regulating zinc ion homeostasis and zinc ion supplementation has potential as a therapy for psoriasis.

Comparison of DNA targeting CRISPR editors in human cells.

BACKGROUND: Profiling and comparing the performance of current widely used DNA targeting CRISPR systems provide the basic information for the gene-editing toolkit and can be a useful resource for this field. In the current study, we made a parallel comparison between the recently reported miniature Cas12f1 (Un1Cas12f1 and AsCas12f1) and the widely used Cas12a and Cas9 nucleases in mammalian cells. RESULTS: We found that as a CRISPRa activator, Un1Cas12f1 could induce gene expression with a comparable level to that of Cas12a and Cas9, while as a DNA cleavage editor, Cas12f1 exhibited similar properties to Cas12a, like high specificity and dominantly induced deletions over insertions, but with less activity. In contrast, wild-type SpCas9 showed the highest activity, lowest specificity, and induced balanced deletions and insertions. Thus, Cas12f1 is recommended for gene-activation-based applications, Cas12a is for therapy applications, and wild-type Cas9 is for in vitro and animal investigations. CONCLUSION: The comparison provided the editing properties of the widely used DNA-targeting CRISPR systems in the gene-editing field.

Engineered Cas12a-Plus nuclease enables gene editing with enhanced activity and specificity.

BACKGROUND: The CRISPR-Cas12a (formerly Cpf1) system is a versatile gene-editing tool with properties distinct from the broadly used Cas9 system. Features such as recognition of T-rich protospacer-adjacent motif (PAM) and generation of sticky breaks, as well as amenability for multiplex editing in a single crRNA and lower off-target nuclease activity, broaden the targeting scope of available tools and enable more accurate genome editing. However, the widespread use of the nuclease for gene editing, especially in clinical applications, is hindered by insufficient activity and specificity despite previous efforts to improve the system. Currently reported Cas12a variants achieve high activity with a compromise of specificity. Here, we used structure-guided protein engineering to improve both editing efficiency and targeting accuracy of Acidaminococcus sp. Cas12a (AsCas12a) and Lachnospiraceae bacterium Cas12a (LbCas12a). RESULTS: We created new AsCas12a variant termed "AsCas12a-Plus" with increased activity (1.5~2.0-fold improvement) and specificity (reducing off-targets from 29 to 23 and specificity index increased from 92% to 94% with 33 sgRNAs), and this property was retained in multiplex editing and transcriptional activation. When used to disrupt the oncogenic BRAFV600E mutant, AsCas12a-Plus showed less off-target activity while maintaining comparable editing efficiency and BRAFV600E cancer cell killing. By introducing the corresponding substitutions into LbCas12a, we also generated LbCas12a-Plus (activity improved ~1.1-fold and off-targets decreased from 20 to 12 while specificity index increased from 78% to 89% with 15 sgRNAs), suggesting this strategy may be generally applicable across Cas12a orthologs. We compared Cas12a-Plus, other variants described in this study, and the reported enCas12a-HF, enCas12a, and Cas12a-ultra, and found that Cas12a-Plus outperformed other variants with a good balance for enhanced activity and improved specificity. CONCLUSIONS: Our discoveries provide alternative AsCas12a and LbCas12a variants with high specificity and activity, which expand the gene-editing toolbox and can be more suitable for clinical applications.

Potential value and chemical characterization of gut microbiota derived nitrogen containing metabolites in feces from Periplaneta americana (L.) at different growth stages.

The American cockroach, Periplaneta americana (L.), is able to highly survive in various complicated environments around the globe, and often considered as a pest. In contrast, billions of P. americana have been massively reared in China and extensively used as a medicinal insect, due to its function for preventing and treating ulceration and heart failure. Considering the possibility that microbiota-derived metabolites could be an effective source to identify promising candidate drugs, we attempted to establish a rapid method for simultaneous determination of gut microbiota metabolites from medicinal insects. In this study, network pharmacology approach and ultra-performance liquid chromatography (UPLC) technique were employed to reveal the potential pharmacological activity and dynamics variation of nitrogen-containing metabolites (NCMs) originated from the gut microbiota of breeding P. americana at different growth stages. A metabolites-targets-diseases network showed that NCMs are likely to treat diseases such as ulceration and cancer. The analysis of NCMs' content with the growth pattern of P. americana indicated that the content of NCMs declined with P. americana aging. Both principal component analysis and orthogonal partial least squares discriminant analysis suggested that 8-hydroxy-2-quinolinecarboxylic acid and 8-hydroxy-3,4-dihydro-2(1H)-quinolinone are the potential differential metabolic markers for discriminating between nymphs and adults of P. americana. Moreover, the developed UPLC method showed an excellent linearity (R2 > 0.999), repeatability (RSD < 2.6%), intra- and inter-day precisions (RSD < 2.2%), and recovery (95.5%-99.0%). Collectively, the study provides a valuable strategy for analyzing gut microbiota metabolites from insects and demonstrates the prospects for discovering novel drug candidates from the feces of P. americana.

Combining miR-23b exposure with mesenchymal stem cell transplantation enhances therapeutic effects on EAE.

Bone marrow mesenchymal stem cells (BMSCs) have the immuno-modulatory capacity to ameliorate autoimmune diseases, such as multiple schlerosis (MS), systemic lupus erythematosus and rheumatoid arthritis. However, BMSC-mediated immunosuppression can be challenging to achieve. The efficacy of BMSC transplantation may be augmented by an adjuvant therapy. Here, we demonstrated that treatment of mice with experimental autoimmune encephalomyelitis (EAE), a model of MS, with BMSCs over-expressing microRNA (miR)-23b provided better synergistic and longer-term therapeutic effects than treatment with traditional BMSCs. Over-expression of miR-23b enhanced the ability of BMSCs to inhibit differentiation of Th17 cells and reduced IL-17 secretion. Compared to traditional BMSCs, the miR-23b over-expressing BMSCs (miR23b-BMSCs) exhibited enhanced secretion of tumor growth factor beta 1 (TGF-ß1), a cytokine that promotes the differentiation of regulatory T (Treg) cells. Pathologically, miR23b-BMSC transplantation delayed EAE progression, apparently by reducing the Th17/Treg cell ratio and inhibiting inflammatory cell infiltration across the blood-brain barrier, and thus slowing spinal cord demyelination. These results may lead to better utility of BMSCs as a treatment for autoimmune diseases.

Neural-specific distribution of transmembrane protein TMEM240 and formation of TMEM240-Body.

Mutation in TMEM240 is suggested to cause SCA21, but the specific mechanism has not been clarified. The subcellular localization, specific biological function, and corresponding mechanism of action of TMEM240 have also not been delineated. In this study, the mRNA and protein expression of TMEM240 were assessed using qPCR and western blotting, respectively. Live cell imaging was used to establish the sub-cellular location of TMEM240, and electron microscopy was used to determine the morphology and distribution of TMEM240 in the cell. TMEM240 was specifically expressed in the neurons. Exogenous TMEM240 formed a multilayered cell structure, which we refer to as TMEM240-Body (T240-Body). T240-Body was separated and purified by centrifugation and filtration. An anchor protein His-tagged-GFP-BP on Ni-NTA agarose was used to pull down T240-GFP binding proteins. Both the N-terminal and the C-terminal of TMEM240 were confirmed to be inside the T240-Body. Co-localization experiments suggested that peroxisomes might contribute to T240-Body formation, and the two transmembrane regions of TMEM240 appear to be essential for formation of the T240-Body. Emerin protein contributed to formation of T240-Body when combined with TMEM240. Overall, this study provides new insights into TMEM240, which inform future research to further our understanding of its biological function.

Differentiating prostate cancer from benign prostatic hyperplasia using PSAD based on machine learning: Single-center retrospective study in China.

The incidence of prostate cancer increases annually. Prostate cancer is an underreported and emerging problem in China. We conducted a cross-sectional study of 392 eligible patients from 710 men with prostate cancer or benign prostatic hyperplasia between 2000 and 2003. For total prostate-specific antigen, age, three diameters of prostate, prostate volume and prostate-specific antigen density seven indices, analysis of variance and t test were used to analyze the difference between the groups. A decision tree with pruning was established using the prostate-specific antigen density, age and transversal diameter of the prostate to screen the patient with prostate cancer. According to the established decision tree model, prostate-specific antigen density was the most important factor affecting the occurrence of prostate cancer. In elderly people over the age of 83 years, the transverse diameter of prostate cancer was smaller than that of benign prostatic hyperplasia, with prostate-specific antigen density less than . No additional index was introduced, and the detection rate of prostate cancer was 86.6 %.The specificity was enhanced to 78.1%.

Association between serum magnesium and common complications of diabetes mellitus.

BACKGROUND: Magnesium ion, as important cation in the human body, involved in various enzymatic reactions, glucose transport and insulin release. Now diabetes mellitus and diabetic complications have become important public health problems around the world. OBJECTIVE: This paper explores the association between concentration levels of serum magnesium and common complications and comorbidities of diabetes mellitus and other biochemical indexes. METHODS: There are 1217 eligible patients selected from 14,317 cases of diabetic hospitalization patients from January 2010 to December 2011. Random forest algorithm was applied to assess the importance of various biochemical indexes and to perform diabetic complications prediction. RESULTS: The research results showed that low concentration of serum magnesium and four common diabetic complications - diabetic retinopathy, diabetic nephropathy, diabetic neuropathy and diabetic macroangiopathy - exists association, but no obvious correlation with other comorbidities like hypertension. CONCLUSIONS: The specific factors of four common diabetic complications were selected from the biochemical indexes to provide a reference direction for further research.

Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

BACKGROUND: Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. METHODS: In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. RESULTS: The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. CONCLUSIONS: No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.