Enhanced Response of Acute Monocytic Leukemia Cells to Low-dose Cytarabine by 1,25-dihydroxyvitamin D3

Low-dose cytarabine combined with differentiating or DNA hypomethylating agents,such as vitamin D compounds,is a potential regimen to treat acute myeloid leukemia（AML） patients who are unfit for high-intensity chemotherapy.The present study aimed to determine which subset of AML would be most responsive to low-dose cytarabine with the differentiating agent 1,25-dihydroxyvitamin D3（1,25-D3）.Here,firstly,c Bio Portal database was used and we found out that vitamin D receptor（VDR） was highly expressed in acute monocytic leukemia（M5） and high VDR expression was associated with a poor survival of AML patients.Then,we confirmed that 1,25-D3 at clinical available concentration could induce more significant differentiation in acute monocytic leukemia cell lines（U937,MOLM-13,THP-1） and blasts from M5 patients than in non-monocytic cell lines（KG1 a and K562） and blasts from M2 patient.Finally,it was shown that the combination of 1,25-D3 and low-dose cytarabine further increased the differentiating rate,growth inhibition and G0/G1 arrest,while mild changes were found in the apoptosis in acute monocytic leukemia cell lines.Our study demonstrates that the enhanced response of acute monocytic leukemia cells to low-dose cytarabine by 1,25-D3 might indicate a novel therapeutic direction for patients with acute monocytic leukemia,especially for elderly and frail ones.

Interferon-γ Alters the Immune-related miRNA Expression of Microvesicles Derived from Mesenchymal Stem Cells

Increasing studies have demonstrated that interferon gamma（IFN-γ）,which serves as a critical inflammatory cytokine,is essential to induce the immunosuppressive effects of mesenchymal stem cells（MSCs）.However,the mechanisms underlying the enhanced immunosuppressive effects of IFN-γ-stimulated MSCs（γMSCs） are not fully understood.MSC-derived microvesicles（MSC-MVs） have been viewed as potential pivotal mediators of the immunosuppressive effects of MSCs.Moreover,micro RNAs（miR NAs） are important regulators of immunological processes and can be shuttled from cell to cell by MVs.The aim of our study was to analyze the the mi RNA expression signature of MVs derived from γMSCs（γMSC-MVs）,which may provide better understanding of the immunosuppressive property of their parent cells.Through mi RNA microarray and bioinformatics analysis,we found 62 significantly differentially expressed miR NAs（DEMs） in γMSC-MVs compared with MSC-MVs.And the potential target genes and signaling pathways regulated by DEMs were predicted and analyzed.Interestingly,many DEMs and predicted signaling pathways had been demonstrated to be involved in immunoregulation.Furthermore,the network between immunoregulation-related pathways and relevant DEMs was constructed.Collectively,our research on the mi RNA repertoires of γMSC-MVs not only provides new perspectives into the mechanisms underlying the enhanced immunosuppressive property of γMSCs,but also paves the way to clinical application of these potent organelles in the future.

hTFtarget:A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets

Transcription factors(TFs)as key regulators play crucial roles in biological processes.The identification of TF-target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression.The accumulated data of chromatin immunoprecipitation sequencing(ChIP-seq)provide great opportunities to discover the TF-target regulations across different conditions.In this study,we constructed a database named hTFtarget,which integrated huge human TF target resources(7190 ChIP-seq samples of 659 TFs and high-confidence binding sites of 699 TFs)and epigenetic modification information to predict accurate TF-target regulations.hTFtarget offers the following functions for users to explore TF-target regulations:(1)browse or search general targets of a query TF across datasets;(2)browse TF-target regulations for a query TF in a specific dataset or tissue;(3)search potential TFs for a given target gene or noncoding RNA;(4)investigate co-association between TFs in cell lines;(5)explore potential coregulations for given target genes or TFs;(6)predict candidate TF binding sites on given DNA sequences;(7)visualize ChIP-seq peaks for different TFs and conditions in a genome browser.hTFtarget provides a comprehensive,reliable and user-friendly resource for exploring human TF-target regulations,which will be very useful for a wide range of users in the TF and gene expression regulatiol community.hTFtarget is available at bttp://bioinfo.life.hust.edu.cn/hTFtarget.

Transcriptome and Regulatory Network Analyses of CD19-CAR-T Immunotherapy for B-ALL

Chimeric antigen receptor (CAR) T cell therapy has exhibited dramatic anti-tumor effi-cacy in clinical trials. In this study,we reported the transcriptome profiles of bone marrow cells in four B cell acute lymphoblastic leukemia (B-ALL) patients before and after CD19-specific CAR-T therapy. CD19-CAR-T therapy remarkably reduced the number of leukemia cells,and three patients achieved bone marrow remission (minimal residual disease negative). The efficacy of CD19-CAR-T therapy on B-ALL was positively correlated with the abundance of CAR and immune cell subpopulations,e.g.,CD8+T cells and natural killer (NK) cells,in the bone marrow. Additionally,CD19-CAR-T therapy mainly influenced the expression of genes linked to cell cycle and immune response pathways,including the NK cell mediated cytotoxicity and NOD-like recep-tor signaling pathways. The regulatory network analyses revealed that microRNAs (e.g.,miR-148a-3p and miR-375),acting as oncogenes or tumor suppressors,could regulate the crosstalk between the genes encoding transcription factors (TFs,e.g.,JUN and FOS) and histones (e.g.,HIST1H4A and HIST2H4A) involved in CD19-CAR-T therapy. Furthermore,many long non-coding RNAs showed a high degree of co-expression with TFs or histones (e.g.,FOS and HIST1H4B) and were associated with immune processes. These transcriptome analyses provided important clues for fur-ther understanding the gene expression and related mechanisms underlying the efficacy of CAR-T immunotherapy.

生物信息学资源助力蛋白质磷酸化的系统层次理解

Protein phosphorylation,catalyzed by protein kinases(PKs),is one of the most prevalent post-translational modifications(PTMs)in eukaryotes.Phosphorylation occurring at different positions in a protein sequence can possess distinct functional impacts,and sitespecific phosphorylation may drastically alter a protein’s conformation,activity,and trafficking.Traditionally,biologists usually focused on studying regulatory mechanisms of phosphorylation in a limited number of proteins,mainly due to a lack of highthroughput technology.During the past two decades,advances in liquid chromatography coupled with tandem mass spectrometry(LC-MS/MC)have boomed a revolutionary technology named phosphoproteomics,which can simultaneously quantify thousands of phosphorylation sites(p-sites),and provide a great opportunity for a systems-level understanding of phosphorylation.Besides LCMS/MC,other approaches such as immunohistochemistry(IHC)and immune-detection by sequencing(ID-seq)have also emerged.

Stereotypes About Enterotype: the Old and New Ideas

In 2011, the term ‘‘enterotype" first appeared to the general public in Nature, which refers to stratification of human gut microbiota. However, with more studies on enterotypes conducted nowadays, doubts about the existence and robustness of enterotypes have also emerged. Here we reviewed current opinions about enterotypes from both conceptual and analytical points of view.We firstly illustrated the definition of the enterotype and various factors influencing enterotypes,such as diet, administration of antibiotics, and age. Then we summarized lines of evidence that pose the concept against the enterotype, and described the current methods for enterotype analysis.Finally, we showed that the concept of enterotype has been extended to other ecological niches.Based on current studies on enterotypes, it has been clear that more studies with larger sample sizes are needed to characterize the enterotypes. Improved computational methods are also required to build sophisticated models, reflecting the dynamics and resilience of enterotypes.

Consistent Alterations of Human Fecal Microbes After Transplantation into Germ-free Mice

Fecal microbiota transplantation(FMT)of human fecal samples into germ-free(GF)mice is useful for establishing causal relationships between the gut microbiota and human phenotypes.However,due to the intrinsic differences between human and mouse intestines and the different diets of the two organisms,it may not be possible to replicate human phenotypes in mice through FMT;similarly,treatments that are effective in mouse models may not be effective in humans.In this study,we aimed to identify human gut microbes that undergo significant and consistent changes(i.e.,in relative abundances)after transplantation into GF mice in multiple experimental settings.We collected 16S rDNA-seq data from four published studies and analyzed the gut microbiota profiles from 1713 human–mouse pairs.Strikingly,on average,we found that only 47%of the human gut microbes could be re-established in mice at the species level,among which more than 1/3 underwent significant changes(referred to as“variable taxa”).Most of the human gut microbes that underwent significant changes were consistent across multiple human–mouse pairs and experimental settings.Consequently,about 1/3 of human samples changed their enterotypes,i.e.,significant changes in their leading species after FMT.Mice fed with a controlled diet showed a lower enterotype change rate(23.5%)than those fed with a noncontrolled diet(49.0%),suggesting a possible solution for rescue.Most of the variable taxa have been reported to be implicated in human diseases,with some recognized as the causative species.Our results highlight the challenges of using a mouse model to replicate human gut microbiota-associated phenotypes,provide useful information for researchers using mice in gut microbiota studies,and call for additional validations after FMT.An online database named FMT-DB is publicly available at http://fmt2mice.humangut.info/#/.

HybridSucc:A Hybrid-learning Architecture for General and Species-specific Succinylation Site Prediction

As an important protein acylation modification,lysine succinylation(Ksucc)is involved in diverse biological processes,and participates in human tumorigenesis.Here,we collected 26,243 non-redundant known Ksucc sites from 13 species as the benchmark data set,combined 10 types of informative features,and implemented a hybrid-learning architecture by integrating deep-learning and conventional machine-learning algorithms into a single framework.We constructed a new tool named HybridSucc,which achieved area under curve(AUC)values of 0.885 and 0.952 for general and human-specific prediction of Ksucc sites,respectively.In comparison,the accuracy of HybridSucc was 17.84%-50.62%better than that of other existing tools.Using HybridSucc,we conducted a proteome-wide prediction and prioritized 370 cancer mutations that change Ksucc states of 218 important proteins,including PKM2,SHMT2,and IDH2.We not only developed a high-profile tool for predicting Ksucc sites,but also generated useful candidates for further experimental consideration.The online service of HybridSucc can be freely accessed for academic research at http://hybridsucc.biocuckoo.org/.

GAAD: A Gene and Autoimmiune Disease Association Database

Autoimmune diseases （ADs） arise from an abnormal immune response of the body against substances and tissues normally present in the body. More than a hundred of ADs have been described in the literature so far. Although their etiology remains largely unclear, various types of ADs tend to share more associated genes with other types of ADs than with non-AD types. Here we present GAAD, a gene and AD association database. In GAAD, we collected 44,762 associations between 49 ADs and 4249 genes from public databases and MEDLINE documents. We manually verified the associations to ensure the quality and credibility. We reconstructed and recapitulated the relationships among ADs using their shared genes, which further validated the quality of our data. We also provided a list of significantly co-occurring gene pairs among ADs;with embedded tools, users can query gene co-occurrences and construct customized cooccurrence network with genes of interest. To make GAAD more straightforward to experimental biologists and medical scientists, we extracted additional information describing the associations through text mining, including the putative diagnostic value of the associations, type and position of gene polymorphisms, expression changes of implicated genes, as well as the phenotypical consequences, and grouped the associations accordingly. GAAD is freely available at http：//gaad.medgenius.info.

Selection for Cheaper Amino Acids Drives Nucleotide Usage at the Start of Translation in Eukaryotic Genes

Coding regions have complex interactions among multiple selective forces,which are manifested as biases in nucleotide composition.Previous studies have revealed a decreasing GC gradient from the 5′-end to 3′-end of coding regions in various organisms.We confirmed that this gradient is universal in eukaryotic genes,but the decrease only starts from the~25th codon.This trend is mostly found in nonsynonymous(ns)sites at which the GC gradient is universal across the eukaryotic genome.Increased GC contents at ns sites result in cheaper amino acids,indicating a universal selection for energy efficiency toward the N-termini of encoded proteins.Within a genome,the decreasing GC gradient is intensified from lowly to highly expressed genes(more and more protein products),further supporting this hypothesis.This reveals a conserved selective constraint for cheaper amino acids at the translation start that drives the increased GC contents at ns sites.Elevated GC contents can facilitate transcription but result in a more stable local secondary structure around the start codon and subsequently impede translation initiation.Conversely,the GC gradients at four-fold and two-fold synonymous sites vary across species.They could decrease or increase,suggesting different constraints acting at the GC contents of different codon sites in different species.This study reveals that the overall GC contents at the translation start are consequences of complex interactions among several major biological processes that shape the nucleotide sequences,especially efficient energy usage.

Micro-coevolution of host genetics with gut microbiome in three Chinese ethnic groups

Understanding the micro-coevolution of the human gut microbiome with host genetics is challenging but essential in both evolutionary and medical studies.To gain insight into the interactions between host genetic variation and the gut microbiome,we analyzed both the human genome and gut microbiome collected from a cohort of 190 students in the same boarding college and representing 3 ethnic groups,Uyghur,Kazakh,and Han Chinese.We found that differences in gut microbiome were greater between genetically distinct ethnic groups than those genetically closely related ones in taxonomic composition,functional composition,enterotype stratification,and microbiome genetic differentiation.We also observed considerable correlations between host genetic variants and the abundance of a subset of gut microbial species.Notably,interactions between gut microbiome species and host genetic variants might have coordinated effects on specific human phenotypes.Bacteroides ovatus,previously reported to modulate intestinal immunity,is significantly correlated with the host genetic variant rs12899811(meta-P=5.55×10^(-5)),which regulates the VPS33B expression in the colon,acting as a tumor suppressor of colorectal cancer.These results advance our understanding of the micro-coevolution of the human gut microbiome and their interactive effects with host genetic variation on phenotypic diversity.

lncRInter:A database of experimentally validated long non-coding RNA interaction

Non-coding regions are the major component of human genomes and the long non-coding RNA（IncRNA）is a class of pervasive genes located in noncoding regions（Morris and Mattick,2014）.IncRNAs play a wide range of regulatory roles in gene transcription,translation,epigenetic modification and protein function by interacting with different types of molecules including DNA,

GAN-GMHI: a generative adversarial network with high discriminative power for microbiome-based disease prediction

With the rapid development of research on the human gut microbiome,associations between the microbiome and various complex chronic diseases have been revealed(Bergot et al.,2019).These advancements provide great opportunities for studying the roles of the microbiome in disease prediction(Kashyap et al.,2017).

Agricultural Risk Factors Influence Microbial Ecology in Honghu Lake

Agricultural activities, including stock-farming, planting industry, and fish aquaculture,can affect the physicochemical and biological characters of freshwater lakes. However, the effects of pollution producing by agricultural activities on microbial ecosystem of lakes remain unclear.Hence, in this work, we selected Honghu Lake as a typical lake that is influenced by agriculture activities. We collected water and sediment samples from 18 sites, which span a wide range of areas from impacted and less-impacted areas. We performed a geospatial analysis on the composition of microbial communities associated with physicochemical properties and antibiotic pollution of samples. The co-occurrence networks of water and sediment were also built and analyzed. Our results showed that the microbial communities of impacted and less-impacted samples of water were largely driven by the concentrations of TN, TP, NO_3^--N, and NO_2^--N, while those of sediment were affected by the concentrations of Sed-OM and Sed-TN. Antibiotics have also played important roles in shaping these microbial communities: the concentrations of oxytetracycline and tetracycline clearly reflected the variance in taxonomic diversity and predicted functional diversity between impacted and less-impacted sites in water and sediment samples, respectively. Furthermore, for samples from both water and sediment, large differences of network topology structures between impacted and less-impacted were also observed. Our results provide compelling evidence that the microbial community can be used as a sentinel of eutrophication and antibiotics pollution risk associated with agricultural activity; and that proper monitoring of this environment is vital to maintain a sustainable environment in Honghu Lake.

Precision Medicine:What Challenges Are We Facing?

Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several nations have announced that their national research programs would definitely head toward this direction. Now,

The Fast Track for Microbiome Research

The microbiome research is undoubtedly one of the most popular topics in biomedical research areas.This is not without reason:given that microbiome is found to be linked with and sometime causes chronic diseases and even cancers,it has become more and more obvious that microbiome plays crucial roles in human health and the surrounding environments.

Microbial Dark Matter: from Discovery to Applications

With the rapid increase of the microbiome samples and sequencing data,more and more knowledge about microbial communities has been gained.However,there is still much more to learn about microbial communities,including billions of novel species and genes,as well as countless spatiotemporal dynamic patterns within the microbial communities,which together form the microbial dark matter.In this work,we summarized the dark matter in microbiome research and reviewed current data mining methods,especially artificial intelligence(AI)methods,for different types of knowledge discovery from microbial dark matter.We also provided case studies on using AI methods for microbiome data mining and knowledge discovery.In summary,we view microbial dark matter not as a problem to be solved but as an opportunity for AI methods to explore,with the goal of advancing our understanding of microbial communities,as well as developing better solutions to global concerns about human health and the environment.

Protist 10,000 Genomes Project

Protists are a highly diverse group of microscopic eukaryotic organisms that are not fungi,animals,or plants.Protistswere some of the microbes first visualized and described by Anton van Leeuwenhoek using themicroscope in the seventeenth century.After that,the description and cataloging of these diverse microbial eukaryotes was pursued by microbiologists throughout the following centuries.1 So far,more than 60,000 protist species have been recorded in the NCBI taxonomy system,but many have yet to be identified.Protists have long been considered important models in fundamental biological studies,such as cell biology,genetics,ecology and evolution toxicology,and applied fields,including biofuels,nutritional supplements and aquaculture feed production,environmental monitoring and pollution treatment,protozoan parasitic disease treatment and prevention,as well as agriculture.