Biology subjects
Publications and source records attributed to Ma, S..
The paper with the doi 10.1101/850305 has been removed as a result of a technical error. The paper is available on bioRxiv under this doi: 10.1101/2019.12.14.850305.
The lipopolysaccharide biosynthesis pathway is considered an attractive drug target against the rising threat of multidrug-resistant Gram-negative bacteria. Here, we report two novel small-molecule inhibitors (compounds 1 and 2) of the acyltransferase LpxA, the first enzyme in the lipopolysaccharide biosynthesis pathway. We show genetically that the antibacterial activities of the compounds against efflux-deficient Escherichia coli are mediated by LpxA inhibition. Consistently, the compounds inhibited the LpxA enzymatic reaction in vitro. Intriguingly, using biochemical, biophysical, and structural characterization, we reveal two distinct mechanisms of LpxA inhibition; compound 1 is a substrate-competitive inhibitor targeting apo LpxA and compound 2 is an uncompetitive inhibitor targeting the LpxA-product complex. Compound 2 exhibited more favorable biological and physicochemical properties than compound 1, and was optimized using structural information to achieve improved antibacterial activity against wild type E. coli. These results show that LpxA is a promising antibacterial target and imply the advantages of targeting enzyme-product complexes in drug discovery.
Huntington disease (HD) manifests in both adult and juvenile forms. Mutant HTT gene carriers are thought to undergo normal brain development followed by a degenerative phase, resulting in progressive clinical manifestations. However, recent studies in children and prodromal individuals at risk for HD have raised the possibility of abnormal neurodevelopment. Although key findings in rodent models support this notion, direct evidence in the context of human physiology remains lacking. Using a panel of isogenic HD human embryonic pluripotent stem cells and cerebral organoids, we investigated the impact of mutant HTT on early neurodevelopment. We find that ventricular zone-like neuroepithelial progenitor layer expansion is blunted in an HTT CAG repeat length-dependent manner due to premature neurogenesis in HD cerebral organoids, driven by cell intrinsic processes. Transcriptional profiling and imaging analysis revealed impaired cell cycle regulatory processes, increased G1 length, and increased asymmetric division of apical progenitors, collectively contributing to premature neuronal differentiation. We demonstrate increased activity of the ATM-p53 pathway, an up-stream regulator of cell cycle processes, and show that treatment with ATM antagonists partially rescues the blunted neuroepithelial progenitor expansion in HD organoids. Our findings suggest that CAG repeat length regulates the balance between neural progenitor expansion and differentiation during early neurodevelopment. Our results further support the view that HD, at least in its early-onset forms, may not be a purely neurodegenerative disorder, and that abnormal neurodevelopment may be a component of HD pathophysiology.
A widespread assumption for single-cell analyses specifies that one cells nucleic acids are predominantly captured by one oligonucleotide barcode. However, we show that [~]13-21% of cell barcodes from the 10x Chromium scATAC-seq assay may have been derived from a droplet with more than one oligonucleotide sequence, which we call \"barcode multiplets\". We demonstrate that barcode multiplets can be derived from at least two different sources. First, we confirm that [~]4% of droplets from the 10x platform may contain multiple beads. Additionally, we find that [~]5-7% of beads may contain multiple oligonucleotide barcodes. We show that this artifact can confound single-cell analyses, including the interpretation of clonal diversity and proliferation of intra-tumor lymphocytes. Overall, our work provides a conceptual and computational framework to identify and assess the impacts of barcode multiplets in single-cell data.
Singing by songbirds is a complex motor skill learnt during juvenile development or, in open-ended learners, before the onset of the breeding season. Outside of these specific periods, it is believed that birdsong does not change. Challenging this, here we demonstrate that in a seasonal songbird, social interactions during the breeding season induce a novel form of singing plasticity in naturalistic social environments. Using custom-made telemetric backpack technology to monitor song-based communication from freely-behaving canaries, we show that males temporally overlap their songs during aggressive duels. Singing duels induce an unexpected fast plasticity in song length, thereby enhancing singing performance and flexibility of a sexually-selected behavior. Remarkably, dueling canaries sing acoustically-similar songs, suggesting that competition within a specific song acoustic space drives dueling behavior. Overall, our findings reveal a previously unrecognized type of song plasticity different from the well-studied slow song plasticity as an imitation process for display purposes.
The rapid spread of multi-drug resistant strains has created a pressing need for new drug regimens to treat tuberculosis (TB), which kills 1.8 million people each year. Identifying new regimens has been challenging due to the slow growth of the pathogen M. tuberculosis (MTB), coupled with large number of possible drug combinations. Here we present a computational model (INDIGO-MTB) that identified synergistic regimens featuring existing and emerging anti-TB drugs after screening in silico over 1 million potential drug combinations using MTB drug transcriptomic profiles. INDIGO-MTB further predicted the gene Rv1353c as a key transcriptional regulator of multiple drug interactions, and we confirmed experimentally that Rv1353c up-regulation reduces the antagonism of the bedaquiline-streptomycin combination. Retrospective analysis of 57 clinical trials of TB regimens using INDIGO-MTB revealed that synergistic combinations were significantly more efficacious than antagonistic combinations (p-value = 1 x 10-4) based on the percentage of patients with negative sputum cultures after 8 weeks of treatment. Our study establishes a framework for rapid assessment of TB drug combinations and is also applicable to other bacterial pathogens.\n\nIMPORTANCEMulti-drug combination therapy is an important strategy for treating tuberculosis, the worlds deadliest bacterial infection. Long treatment durations and growing rates of drug resistance have created an urgent need for new approaches to prioritize effective drug regimens. Hence, we developed a computational model called INDIGO-MTB, which identifies synergistic drug regimens from an immense set of possible drug combinations using pathogen response transcriptome elicited by individual drugs. Although the underlying input data for INDIGO-MTB was generated under in vitro broth culture conditions, the predictions from INDIGO-MTB correlated significantly with in vivo drug regimen efficacy from clinical trials. INDIGO-MTB also identified the transcription factor Rv1353c as a regulator of multiple drug interaction outcomes, which could be targeted for rationally enhancing drug synergy.
Heterozygous deletions in the 15q13.3 region are associated with several neuropsychiatric disorders including autism, schizophrenia, and attention deficit hyperactivity disorder. Several genes within the 15q13.3 deletion region may play a role in neuronal dysfunction, based on association studies in humans and functional studies in mice, but the intermediate molecular mechanisms remain unknown. We analyzed the genome-wide effects of the 15q13.3 microdeletion on the transcriptome and epigenome. Induced pluripotent stem cell (iPSC) lines from three patients with the typical heterozygous 15q13.3 microdeletion and three sex-matched controls were generated and converted into induced neurons (iNs) using the neurogenin-2 induction method. We analyzed genome-wide gene expression using RNA-Seq, genome-wide DNA methylation using SeqCap-Epi, and genome-wide chromatin accessibility using ATAC-Seq, in both iPSCs and iNs. In both cell types, gene copy number change within the 15q13.3 microdeletion was accompanied by significantly decreased gene expression and no compensatory changes in DNA methylation or chromatin accessibility, supporting the model that haploinsufficiency of genes within the deleted region drives the disorder. Further, we observed global effects of the deletion on the transcriptome and epigenome, with the effects being cell type specific and occurring at discrete loci. Several genes and pathways associated with neuropsychiatric disorders and neuronal development were significantly altered, including Wnt signaling, ribosome biogenesis, DNA binding, and clustered protocadherins. This molecular systems analysis of a large neuropsychiatric microdeletion can also be applied to other brain relevant chromosomal aberrations to further our etiological understanding of neuropsychiatric disorders.
Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input \"easy Hi-C\" (eHi-C) protocol to map the 3D genome architecture in neurogenesis and brain tissues, and also developed an improved Hi-C bias-correction pipeline (HiCorr) enabling better identification of enhancer loops or aggregates at sub-TAD level. We compared ultra-deep 3D genome maps from 10 human tissue- or cell types, with a focus on stem cells and neural development. We found several large loci in skin-derived human iPSC lines showing recurrent 3D compartmental memory of somatic heterochromatin. Chromatin loop interactions, but not genome compartments, are hallmarks of neural differentiation. Interestingly, we observed many cell type- or differentiation-specific enhancer aggregates spanning large neighborhoods, supporting a phase-separation mechanism that stabilizes enhancer contacts during development. Finally, we demonstrated that chromatin loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.\n\nHighlightsO_LILow input \"easy Hi-C\" protocol compatible with 50-100K cells\nC_LIO_LIImproved Hi-C bias correction allows direct observation and accurate identification of sub-TAD chromatin loops and enhancer aggregates\nC_LIO_LIRecurrent architectural memory of somatic heterochromatin at compartment level in skin-derived hiPSCs\nC_LIO_LIChromatin loop, but not genome compartment, marks neural differentiation\nC_LIO_LIChromatin loop outperforms eQTL in defining brain GWAS target genes\nC_LI
Spatial heterogeneity is a fundamental feature of the tumor microenvironment (TME), and tackling spatial heterogeneity in neoplastic metabolic aberrations is critical for tumor treatment. Genome-scale metabolic network models have been used successfully to simulate cancer metabolic networks. However, most models use bulk gene expression data of entire tumor biopsies, ignoring spatial heterogeneity in the TME. To account for spatial heterogeneity, we performed spatially-resolved metabolic network modeling of the prostate cancer microenvironment. We discovered novel malignant-cell-specific metabolic vulnerabilities targetable by small molecule compounds. We predicted that inhibiting the fatty acid desaturase SCD1 may selectively kill cancer cells based on our discovery of spatial separation of fatty acid synthesis and desaturation. We also uncovered higher prostaglandin metabolic gene expression in the tumor, relative to the surrounding tissue. Therefore, we predicted that inhibiting the prostaglandin transporter SLCO2A1 may selectively kill cancer cells. Importantly, SCD1 and SLCO2A1 have been previously shown to be potently and selectively inhibited by compounds such as CAY10566 and suramin, respectively. We also uncovered cancer-selective metabolic liabilities in central carbon, amino acid, and lipid metabolism. Our novel cancer-specific predictions provide new opportunities to develop selective drug targets for prostate cancer and other cancers where spatial transcriptomics datasets are available.
The length and complexity of tuberculosis (TB) therapy, as well as the propensity of Mycobacterium tuberculosis to develop drug resistance, are major barriers to global TB control efforts. M. tuberculosis is known to have the ability to enter into a drug-tolerant state, which may explain many of these impediments to TB treatment. We have identified a novel mechanism of genetically encoded but rapidly reversible drug-tolerance in M. tuberculosis caused by transient frameshift mutations in a homopolymeric tract (HT) of seven cytosines (7C) in the glpK gene. Inactivating frameshift mutations associated with the 7C HT in glpK produce small colonies that exhibit heritable multi-drug increases in minimal inhibitory concentrations and decreases in drug-dependent killing; however, reversion back to a fully drug-susceptible large-colony phenotype occurs rapidly through the introduction of additional insertions or deletions in the same glpK HT region. These reversible frameshift mutations in the 7C HT of M. tuberculosis glpK occur in clinical isolates, accumulate in M. tuberculosis infected mice with further accumulation during drug treatment, and exhibit a reversible transcriptional profile including induction of dosR and sigH and repression of kstR regulons, similar to that observed in other in vitro models of M. tuberculosis tolerance. These results suggest that GlpK phase variation may contribute to drug-tolerance, treatment failure and relapse in human TB. Drugs effective against phase-variant M. tuberculosis may hasten TB treatment and improve cure rates.\n\nSIGNIFICANCEThe ability of M. tuberculosis to survive during prolonged treatment has been attributed to either transient stress responses or fixed heritable drug-resistance producing mutations. We show that phase-variation in the M. tuberculosis glpK gene represents a third type of resistance mechanism. The ability of these glpK mutants to grow slowly and then rapidly revert suggests that these transiently-heritable changes may also explain how a hidden population of drug-tolerant bacteria develops during TB treatment. As a genetically trackable cause of drug-tolerance, M. tuberculosis glpK mutants provides a unique opportunity to study these phenomena at a cellular and mechanistic level. These mutants could also be used for developing drugs that target tolerant populations, leading to more rapid and effective TB treatments.
Adenine base editor (ABE) mediates the conversion of A to G in genomic DNA. In human, approximately 47.8% of known pathogenic SNPs can be corrected by A to G conversion, indicating that ABE have tremendous potential in gene therapy. However, the off-target activity of ABE limits its clinical application. ABE off-target activity in DNA is depended on the bonding of Streptococcus pyogenes Cas9 (SpCas9) on off-target sites [1, 2]. Therefore, using high-fidelity Cas9 should be able to improve the specificity of ABE. Based on this, we replaced the wild-type SpCas9 in ABE7.10 with four high-fidelity Cas9s to improve its specificity. The analysis of target deep sequencing data demonstrate that the specificity of e-ABE is substantially improved compared to conventional ABE7.10 in four test sites. But the broad editing window of ABE hampers its application, ABE needs to be optimized to get variants with narrow editing window.
Bone marrow (BM) mesenchymal stem cells (MSCs) are critical components of the BM microenvironment and play an essential role in supporting hematopoiesis. Dysfunction of MSCs is associated with the impaired BM microenvironment that promotes leukemia development. However, whether and how restoration of the impaired BM microenvironment can inhibit leukemia development remain unknown. Using an established leukemia model and the RNA-seq analysis, we discovered functional degeneration of MSCs during leukemia progression. Importantly, intra-BM instead of systemic transfusion of donor healthy MSCs restored the BM microenvironment, thus systemically altering cytokine expression patterns, improving normal hematopoiesis, reducing tumor burden, and ultimately prolonging survival of the leukemia-bearing mice. Donor MSC treatment restored the function of host MSCs and reprogrammed host macrophages to fulfill tissue-repair function. Transfusion of MSC-reprogrammed macrophages largely recapitulated the therapeutic effects of MSCs. Further, we found that donor MSCs reprogrammed macrophages to reduce leukemia burden through autocrine of IL-6. Taken together, our study reveals that donor MSCs reprogram host macrophages to restore the BM microenvironment and inhibit leukemia development, thus offering rationales for local MSC administration as a potentially effective therapy for leukemia.\n\nKey PointsKey Point 1: Intra-BM transfusion of MSCs restores the BM microenvironment, improves thrombopoiesis, and suppresses MDS/MPN initiated by Nras mutation.\n\nKey Point 2: Donor MSCs reprogram macrophages to restore the BM microenvironment, improve thrombopoiesis, and suppress leukemia.
Despite many genes associated with human diseases have been identified, disease mechanisms often remain elusive due to the lack of understanding how disease genes are connected functionally at pathways level. Within biological networks, disease genes likely map to modules whose identification facilitates etiology studies but remains challenging. We describe a systematic approach to identify disease-associated gene modules. A gene co-expression network based on the graphical Gaussian model (GGM) was constructed using the GTEx dataset and assembled into 652 gene modules. Screening these modules identified those with disease genes enrichment for obesity, cardiomyopathy, hypertension, and autism, which illuminated the molecular pathways underlying their pathogenesis. Using mammalian phenotypes derived from mouse models, potential disease candidate genes were identified from these modules. Also analyzed were epilepsy, schizophrenia, bipolar disorder, and depressive disorder, revealing shared and distinct disease modules among brain disorders. Thus, disease genes converge on modules within our GGM gene co-expression network, which provides a general framework to dissect genetic architecture of human diseases.
Better understanding the progression of neural stem cells (NSCs) in the developing cerebral cortex is important for modeling neurogenesis and defining the pathogenesis of neuropsychiatric disorders. Here we used RNA-sequencing, cell imaging and lineage tracing of mouse and human in vitro NSCs to model the generation of cortical neuronal fates. We show that conserved signaling mechanisms regulate the acute transition from proliferative NSCs to committed glutamatergic excitatory neurons. As human telencephalic NSCs developed from pluripotency in vitro, they first transitioned through organizer states that spatially pattern the cortex before generating glutamatergic precursor fates. NSCs derived from multiple human pluripotent lines varied in these early patterning states leading differentially to dorsal or ventral telencephalic fates. This work furthers systematic analysis of the earliest patterning events that generate the major neuronal trajectories of the human telencephalon.
The female upper reproductive tract, including the uterus, fallopian tubes and ovaries, is believed to be a sterile environment. With the improvement of bacterial detection, the theory of the sterile female upper reproductive tract has been frequently challenged in recent years. However, thus far, no researchers have used ovaries as study targets. Six women who were diagnosed with ovarian cancer were included in the cancer group, and ten women who were diagnosed with a noncancerous ovarian condition (including three patients with uterine myoma and seven patients with uterine adenomyosis) were included in the control group. Immunohistochemistry staining using an antibacterial lipopolysaccharide (LPS) antibody was used to confirm the presence of bacteria in the ovarian tissues. In addition, 16S rRNA sequencing was used to compare the differences in the bacteria between ovarian cancer tissues and noncancerous ovarian tissues. BugBase and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) were used to predict the functional composition of the bacteria. Bacterial LPS was present in ovarian cancer tissue and noncancerous ovarian tissue, which implied the presence of bacteria in ovarian tissue. When compared to the noncancerous ovarian bacteria at the phylum level, the cancerous ovarian bacteria were composed of increased Aquificae and Planctomycetes and decreased Crenarchaeota. When predicting metagenomes, gene functions associated with the potentially pathogenic and the oxidative stress-tolerant phenotype were enriched in the ovaries of the cancer group. Forty-six significantly different KEGG pathways existed in the ovarian bacteria of the cancer group compared to that of the control group. Different bacteria compositions were present in cancerous and noncancerous ovarian tissues. Author summaryAbdominal solid viscera have always been believed to be absolutely sterile. With the improvement of bacterial detection, this concept is being challenged. Researchers found some bacteria existed in endometrial diseases, the question of whether the ovaries are sterile is still unclear. Therefore, we assume that the bacteria in ovarian tissue are associated with ovarian cancer. When compared to the noncancerous ovarian bacteria at the phylum level, the cancerous ovarian bacteria were composed of increased Aquificae and Planctomycetes and decreased Crenarchaeota. When predicting metagenomes, gene functions associated with the potentially pathogenic and the oxidative stress-tolerant phenotype were enriched in the ovaries of the cancer group. Forty-six significantly different KEGG pathways existed in the ovarian bacteria of the cancer group compared to that of the control group. Different bacteria compositions were present in cancerous and noncancerous ovarian tissues.
Black swimming dots (BSDs) are nanoscale dot-like contaminants in the dishes of cultured cells. Until now, the identity of BSDs has not yet been determined. In our recent study, we proposed that BSDs per se are nonliving inorganic nanoparticles yet should derive from the cells infected with an unidentified airborne pathogen. We showed the pathogen possessed the characteristics including airborne transmitted, cell-dependent, insensitive to antibiotics, filterable through 0.1 m membrane. These properties prompt us to speculate that the pathogen of BSDs might be one kind of unidentified virus-like organism. However, the imperfection is that we have not isolated this putative pathogen from BSD+ samples [1]. Here, we report a further investigation of finding the virus-like pathogen in the serum and tissue extracts from BSD+ mice. Most importantly, this virus-like pathogen can be reisolated from the BSD+ extracts-inoculated, diseased BSD- cells.\n\nTo de ...
The toxin-antitoxin (TA) modules widely exist in bacteria, and their activities are associated with the persister phenotype of the pathogen Mycobacterium tuberculosis (M. tb). M. tb causes Tuberculosis, a contagious and severe airborne disease. There are ten MazEF TA systems in M. tb, which play important roles in stress adaptation. How the antitoxins antagonize toxins in M. tb or how the ten TA systems crosstalk to each other are of interests, but the detailed molecular mechanisms are largely unclear. MazEF-mt9 is a unique member among the MazEF families due to its tRNase activity, which is usually carried out by the VapC family toxins. Here we present the cocrystal structure of the MazEF-mt9 complex at 2.7 [A]. By characterizing the association mode between the TA pairs through various characterization techniques, we found that MazF-mt9 not only bound its cognate antitoxin, but also the non-cognate antitoxin MazE-mt1, a phenomenon that could be also observed in vivo. Based on our structural and biochemical work, we proposed that the cognate and heterologous interactions among different TA systems work together to relieve MazF-mt9s toxicity to M. tb cells, which may facilitate their adaptation to the stressful conditions encountered during host infection.\n\nIMPORTANCETuberculosis (TB) is one of the most severe contagious diseases. Caused by Mycobacterium tuberculosis (M. tb), it poses a serious threat to human health. Additionally, TB is difficult to cure because of the multipledrug-resistant (MDR) and extensively drug-resistant (XDR) M. tb strains. Toxin-antitoxin (TA) systems have been discovered to widely exist in prokaryotic organisms with diverse roles, normally composed of a pair of molecules that antagonize each other. M. tb has ten MazEF systems, and some of them have been proved to be directly associated with the genesis of persisters and drug-resistance of M. tb. We here report the MazEF-mt9 complex structure, and thoroughly characterized the interactions between MazF-mt9 with MazEs within or outside the MazEF-mt9 family. Our study not only revealed the crosstalks between TA families and its significance to M. tb survival but also offers insights into potential anti-TB drug design.
Deciphering molecular stress response is highly relevant to studies of microbes such as Mycobacterium tuberculosis (MTB), the causative pathogen of tuberculosis (TB) which sickens 10 million people and kills 1.8 million each year1. Prolonged therapy and unfavorable outcomes arise partially because MTB has evolved stress responses to achieve tolerance, wherein MTB persists in otherwise inhibitory drug concentrations by means independent of heritable resistance mutations2-4. Understanding these adaptations and how they are regulated can reveal new biology, including unexplored drug targets and treatment-enhancing strategies. Here, we present a novel network-based genetic screening approach: the Transcriptional Regulator Induced Phenotype (TRIP) screen, which we used to identify previously uncharacterized MTB network adaptations to the first-line drug isoniazid (INH). We found regulators that alter IN ...