Biology subjects

Cai, X.

Publications and source records attributed to Cai, X..

At least 145 records · Page 8Linked to original sources

bioRxiv2020

DPHL: A pan-human protein mass spectrometry library for robust biomarker discovery using Data-Independent Acquisition and Parallel Reaction Monitoring

To answer the increasing need for detecting and validating protein biomarkers in clinical specimens, proteomic techniques are required that support the fast, reproducible and quantitative analysis of large clinical sample cohorts. Targeted mass spectrometry techniques, specifically SRM, PRM and the massively parallel SWATH/DIA technique have emerged as a powerful method for biomarker research. For optimal performance, they require prior knowledge about the fragment ion spectra of targeted peptides. In this report, we describe a mass spectrometric (MS) pipeline and spectral resource to support data-independent acquisition (DIA) and parallel reaction monitoring (PRM) based biomarker studies. To build the spectral resource we integrated common open-source MS computational tools to assemble an open source computational workflow based on Docker. It was then applied to generate a comprehensive DIA pan-human library (DPHL) from 1,096 data dependent acquisition (DDA) MS raw files, and it comprises 242,476 unique peptide sequences from 14,782 protein groups and 10,943 SwissProt-annotated proteins expressed in 16 types of cancer samples. In particular, tissue specimens from patients with prostate cancer, cervical cancer, colorectal cancer, hepatocellular carcinoma, gastric cancer, lung adenocarcinoma, squamous cell lung carcinoma, diseased thyroid, glioblastoma multiforme, sarcoma and diffuse large B-cell lymphoma (DLBCL), as well as plasma samples from a range of hematologic malignancies were collected from multiple clinics in China, the Netherlands and Singapore and included in the resource. This extensive spectral resource was then applied to a prostate cancer cohort of 17 patients, consisting of 8 patients with prostate cancer (PCa) and 9 with benign prostate hyperplasia (BPH), respectively. Data analysis of DIA data from these samples identified differential expressions of FASN, TPP1 and SPON2 in prostate tumors. Thereafter, PRM validation was applied to a larger PCa cohort of 57 patients and the differential expressions of FASN, TPP1 and SPON2 in prostate tumors were validated. As a second application, the DPHL spectral resource was applied to a patient cohort consisting of samples from 19 DLBCL patients and 18 healthy individuals. Differential expressions of CRP, CD44 and SAA1 between DLBCL cases and healthy controls were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supported that DIA-PRM MS pipeline enables robust protein biomarker discoveries.

bioinformatics↗

bioRxiv2019

A novel G protein-biased and subtype selective agonist for a G protein-coupled receptor discovered from screening herbal extracts

Subtype selectivity and functional bias are vital in current drug discovery for G protein-coupled receptors (GPCRs) as selective and biased ligands are expected to yield drug leads with optimal on-target benefits and minimal side-effects. However, structure-based design and medicinal chemistry exploration remain challenging in part because of highly conserved binding pockets within subfamilies. Herein, we present an affinity mass spectrometry approach for screening herbal extracts to identify active ligands of a GPCR, the 5-HT2C receptor. Using this method, we discovered a naturally occurring aporphine 1857 that displayed strong selectivity for activating 5-HT2C without activating the 5-HT2A or 5-HT2B receptors. Remarkably, this novel ligand exhibited exclusive bias towards G protein signaling for which key residues were identified, and it showed comparable in vivo efficacy for food intake suppression and weight loss as the anti-obesity drug, lorcaserin. Our study establishes an efficient approach to discovering novel GPCR ligands by exploring the largely untapped chemical space of natural products.

biochemistry↗

bioRxiv2019

PulseDIA: in-depth data independent acquisition mass spectrometry using enhanced gas phase fractionation

An inherent bottleneck of data independent acquisition (DIA) analysis by Orbitrap-based mass spectrometers is the relatively large window width due to the relatively slow scanning rate compared to TOF. Here we present a novel gas phase separation and MS acquisition method called PulseDIA-MS, which improves the specificity and sensitivity of Orbitrap-based DIA analysis. This is achieved by dividing the ordinary DIA-MS analysis covering the entire mass range into multiple injections for DIA-MS analyses with complementary windows. Using standard HeLa digests, the PulseDIA method identified 69,530 peptide precursors from 9,337 protein groups with ten MS injections of 30 min LC gradient. The PulseDIA scheme containing two complementary windows led to the highest gain of peptide and protein identifications per time unit compared to the conventional 30 min DIA method. We further applied the method to profile the proteome of 18 cholangiocarcinoma (CCA) tissue samples (benign and malignant) from nine patients. PulseDIA identified 7,796 protein groups in these CCA samples, with 14% increase of protein identifications, compared to the conventional DIA method. The missing value for protein matrix dropped by 7% with PulseDIA acquisition. 681 proteins were significantly dysregulated in tumorous CCA samples. Together, we presented and benchmarked an alternative DIA method with higher sensitivity and lower missing rate.

cancer biology↗

bioRxiv2019

Epitope containing short peptides capture distinct IgG serodynamics that enable DIVA for live-attenuated vaccines

Differentiating infected from vaccinated animals (DIVA) strategies have been central enabling techniques in several successful viral disease elimination programs. However, owing to their long and uncertain development process, no DIVA-compatible vaccines are available for many important diseases. We report herein a new DIVA strategy based on hybrid protein-peptide microarrays which can theoretically work with any vaccine. Leading from our findings from Peste des petits ruminants (PPR), we found 4 epitope containing short peptides (ECSPs) which have distinct IgG serodynamics: anti-ECSP IgGs only exist for 10-60 days post vaccination (dpv), while anti-protein IgGs remained at high levels for >1000 dpv. These data enabled design of a DIVA diagnostic microarray containing 4 ECSPs and 3 proteins, which unlike cELISA and VNT, enables ongoing monitoring of serological differences between vaccinated individuals and individuals exposed to the pathogen. For 50 samples after 60 dpv, 20 animals were detected with positive anti-ECSP IgGs, indicating recent infections in vaccinated goat/sheep herds. These DIVA diagnostic microarrays will almost certainly facilitate eradication programs for (re-)emerging pathogens and zoonoses.

immunology↗

bioRxiv2019

A cell-free platform based on nisin biosynthesis for discovering novel lanthipeptides and guiding their overproduction in vivo

Lanthipeptides have extensive therapeutic and industrial applications; however, since many are bactericidal, traditional in vivo platforms are limited in their capacity to discover and mass produce novel lanthipeptides as bacterial organisms are often critical components in these systems. We developed a cell-free protein synthesis (CFPS) platform that enables rapid genome mining, screening and guiding overproduction of lanthipeptides in vivo. For proof-of-concept studies, the type I lanthipeptide, nisin, was selected. Four novel lanthipeptides with anti-bacterial activity were identified among all nisin analogs in the NCBI database in a single day. Further, we coupled the CFPS platform with a screening assay for gram-negative bacterial growth and identified a potent nisin mutant, M5. The titer of nisin and nisin analogs significantly improved with CFPS platform guidance. Owing to the similarities in biosynthesis, our CFPS platform is broadly applicable to other lanthipeptides, provides a universal method for lanthipeptides discovery and overproduction.

synthetic biology↗

bioRxiv2019

Close homologue of L1 sensitizes lung cancer cells to cisplatin and paclitaxel via inhibition Akt pathway

Drug resistance is a serious promble during chemotherapy in lung cancer, which may lead to tumor relapse and further progression. CHL1 was a tumor suppressor in most malignancies, and it was found downregulated in NSCLC cisplatin-resistant cells H460. Thus, in this study, we investigated the role and mechanism of chemoresistance by CHL1 in lung cancer. Human lung adenocarcinoma cell lines A549 and its cisplatin resistant cells (A549/DDP) and paclitaxel resistant cells (A549/PTX) were applied in this research. CHL1 was found obvious downregulation in A549/DDP and A549/PTX cells versus A549 cells. Suppression of CHL1 in A549 cells, promoted cell survival rate and clone formation, decreased cell apoptosis when treated with or without DDP and PTX, respectively. While excessive CHL1 expression in A549/DDP and A549/PTX cells, the results were opposite. Moreover, CHL1 knockdown mediating chemoresistance was reversed by Akt inhibitor SC66 in A549 cells. In summary, overexpression of CHL1 reversed chemoresistance to cisplatin and PTX via suppressing Akt pathway in lung cancer, it was suggested that CHL1 maybe as a potential target for overcome chemoresistance in lung cancer.

cancer biology↗

bioRxiv2019

Arginine-GlcNAcylation of death domain and NleB/SseK proteins is crucial for bacteria pathogenesis by regulating host cell death

Death receptor signaling is critical for cell death, inflammation, and immune homeostasis. Hijacking death receptors and their corresponding adaptors through type III secretion system (T3SS) effectors has been evolved to be a bacterial evasion strategy. NleB from enteropathogenic Escherichia coli (EPEC) and SseK1/2/3 from Salmonella enterica serovar Typhimurium (S. Typhimurium) can modify some death domains involved in death receptor signaling through arginine-GlcNAcylation. This study applied a limited substrate screen from 12 death domain proteins with conserved arginines during EPEC and Salmonella infection and found that NleB from EPEC hijacked death receptor signaling tumor necrosis factor receptor 1 (TNFR1)-associated death domain protein (TRADD), FAS-associated death domain protein (FADD), and receptor-interacting serine/threonine-protein kinase 1 (RIPK1), whereas SseK1 and SseK3 disturbed TNFR signaling through the modification of TRADD Arg235/245 and TNFR1 Arg376, respectively. SseK1 and SseK3 delivered by Salmonella inhibited TNF-- but not TNF-related apoptosis-inducing ligand (TRAIL)-induced cell death, which was consistent with their host substrate recognition specificity. Taking advantage of the substrate specificity of SseK effectors, we found that only SseK1 fully rescued the bacteria colonization deficiency contributed by NleBc in Citrobacter rodentium infection animal model, indicating that TRADD was likely to be the preferred in vivo substrate corresponding to NleB/SseK1-induced bacterial virulence. Furthermore, novel auto-arginine-GlcNAcylation was observed in NleB and SseK1/3, which promoted the enzyme activity. These findings suggest that arginine-GlcNAcylation in death domains and auto-arginine-GlcNAcylation catalyzed by type III-translocated bacterial effector proteins NleB/SseKs are crucial for bacteria pathogenesis in regulating nuclear factor-{kappa}B (NF-{kappa}B) and death receptor signaling pathways. This study provides an insight into the mechanism by which EPEC and Salmonella manipulate death receptor signaling and evade host immune defense through T3SS effectors.\n\nAuthor SummaryEnteropathogenic Escherichia coli (EPEC) and Salmonella enterica serovar Typhimurium (S. Typhimurium) are important food-borne pathogens infecting the intestine. They deliver type III secretion system effector NleB/SseKs to modify host death domain proteins by arginine GlcNAcylation. We screened the modification of 12 death domains containing conserved arginine in human genome by NleB, SseK1, SseK2, and SseK3 through ectopic co-expression and bacterial infection. Unlike multiple death receptor signaling inhibition by NleB, we found that SseK1 and SseK3 specifically hijacked tumor necrosis factor receptor 1 (TNFR1)-mediated death signaling through targeting TNFR1-associated death domain protein (TRADD) and receptor TNFR1, respectively. We identified the modification sites and suggested that TRADD was the in vivo target of NleB in mice infection model by utilizing the substrate specificity of SseK1 and SseK3, which highlighted anti-bacterial infection role of TRADD in death receptor signaling and non-death receptor signaling. In addition to the modification on host death domain substrates, we firstly elucidated the effect of auto-modification of the arginine GlcNAc transferases on the enzymatic activity, which widened our understanding of the newly discovered post translational modification in the process of pathogen-host interaction.

microbiology↗

bioRxiv2019

Olaparib and Enzalutamide synergistically suppress HCC progression via the AR-mediated miR-146a-5p/BRCA1 signaling

Hepatocellular carcinoma (HCC) is one of most common malignant tumors worldwide, however, the treatment for advanced HCC remains unsatisfactory. Here we found that Olaparib, a FDA approved PARP inhibitor, could enhance the cytotoxicity in HCC cells with a lower BRCA1 expression, and suppressing the AR with either Enz or AR-shRNA could further increase the Olaparib sensitivity to better suppress the HCC cell growth via a synergistic mechanism that may involve suppressing the expression of BRCA1 and other DNA damage response (DDR) genes. Mechanism studies revealed that Enz/AR signaling might transcriptional regulting the miR-146a-5p expression via binding to the AREs on its 5 promoter region, which could then lead to suppress the homologous recombination-related BRCA1 expression via direct binding to its 3 UTR of mRNA. Preclinical study using an in vivo mouse model also proved that combined Enz plus Olaparib led to better suppression of the HCC progression. Together, these in vitro/in vivo data suggest that combining Enz and Olaparib may help in the development of a novel therapy to better suppress the HCC progression.

synthetic biology↗

bioRxiv2019

Universal activation mechanism of class A GPCRs

Class A G protein-coupled receptors (GPCRs) influence virtually every aspect of human physiology. GPCR activation is an allosteric process that links agonist binding to G protein recruitment, with the hallmark outward movement of transmembrane helix 6 (TM6). However, what leads to TM6 movement and the key residue-level changes of this trigger remain less well understood. Here, by analyzing over 230 high-resolution structures of class A GPCRs, we discovered a modular, universal GPCR activation pathway that unites previous findings into a common activation mechanism, directly linking the bottom of ligand-binding pocket with G protein-coupling region. We suggest that the modular nature of the universal GPCR activation pathway allowed for the decoupling of the evolution of the ligand binding site, G protein binding region and the residues important for receptor activation. Such an architecture might have facilitated GPCRs to emerge as a highly successful family of proteins for signal transduction in nature.

bioinformatics↗

bioRxiv2019

Too much, too young? Altered corticolimbic axonal innervation and resting state functional connectivity suggests sex-dependent outcomes in a rat model of early life adversity

Adverse early experiences significantly alter behavioral and neural trajectories via aberrant brain maturation. Children with a history of early life stress (ELS) exhibit maladaptive behaviors and increased risk of mental illness later in life. Evidence in ELS-exposed humans identifies a role of atypical corticolimbic development; specifically, within amygdala-prefrontal cortex (PFC) circuits, and show precocially mature task-based corticolimbic functional connectivity (FC). However, the neurobiological substrates of such ELS-driven developmental changes remain unknown. Here, we identify putative neurobiological changes to determine the timeline of developmental perturbations following ELS in rats. Anterograde axonal tracing from basolateral amygdala (BLA) to pre- and infralimbic (PL, IL) PFC was quantified at postnatal days (PD)28, 38, and 48, along with anxiety-like behavior, in maternally separated (ELS) or control reared (CON) male and female rats. Resting state (rs)FC was assessed at PD28 and PD48 in a separate cohort. We report that ELS-exposed female rats show early maturation of BLA-PFC innervation at PD28, with ELS-related changes in males not appearing until PD38. ELS disrupted the maturation of rsFC from PD28 to PD48 in females, with enduring relationships between early rsFC and later anxiety-like behavior. Only transient ELS-related changes in rsFC were seen in male PL. Together, these data provide evidence that female rats may be more vulnerable to the effects of ELS via precocial BLA-PFC innervation, which may drive altered corticolimbic rsFC. These data also provide evidence that increased BLA-IL rsFC is associated with behavioral resiliency following ELS in female rats, providing mechanistic insight into the underlying etiology of adversity-induced vulnerability and resiliency.

neuroscience↗

bioRxiv2019

Bacterial fucosidase enables the production of Bombay red blood cells

We present a method to produce H antigen-deficient red blood cells (RBCs) for transfusion to individuals with anti-H antibodies. A fucosidase from bacteria was heterologously expressed efficiently in E. coli and has been demonstrated to completely remove H antigens on the surface of human RBCs in a facile conversion process. The approach we describe here holds promise for making H-deficient RBCs available for a rare population beyond ABO types.

molecular biology↗

bioRxiv2019

Discovery and Multi-center Verification of Prostate Cancer Protein Biomarkers using Single-shot Short Gradient Microflow SWATH and MRMHR Mass Spectrometry

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.\n\nWe applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set. We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).\n\nOverall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method. Finally, the results showed comparable ability to separate clinical groups.

cancer biology↗

bioRxiv2019

High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification

Formalin-fixed, paraffin-embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here we developed a pressure cycling technology (PCT)-SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B-cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between one to 15 years in a biobank and show a high degree of the proteome pattern similarity between two types histological region of small FFPE samples, i.e. punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of certain degree of biological variations. Applying the method to two independent DLBCL cohorts we identified myeloperoxidase (MPO), a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

biochemistry↗

bioRxiv2019

Direct synthesis of EM-visible gold nanoparticles on genetically encoded tags for single-molecule visualization in cells

Single-molecule visualization in cells with genetically encoded tags for electron microscopy (EM) has been a long-awaited but unimplemented tool for cell biologists. Here, we report an approach for directly synthesizing EM-visible gold nanoparticles (AuNPs) on cysteine-rich tags for single-molecule visualization in cells. We first uncovered an auto-nucleation suppression mechanism that allows specific synthesis of AuNPs on isolated cysteine-rich tags. We next exploited this mechanism to develop an approach for single-molecule detection of proteins in prokaryotic cells and achieved an unprecedented labeling efficiency. We then expanded it to more complicated eukaryotic cells and successfully detected the proteins targeted to various organelles, including the membranes of endoplasmic reticulum (ER) and nuclear envelope, ER lumen, nuclear pores, spindle pole bodies, and mitochondrial matrix. Thus, our implementation of genetically encoded tags for EM should allow cell biologists to address an enormous range of biological questions at single-molecule level in diverse cellular ultrastructural contexts without using antibodies.

biophysics↗

bioRxiv2018

Enrichment of short mutant cell-free DNA fragments enhanced detection of pancreatic cancer

Analysis of cell-free DNA (cfDNA) is promising for broad applications in clinical settings, but with significant bias towards late-stage cancers. Although recent studies have discussed the diverse and degraded nature of cfDNA molecules, little is known about its impact on the practice of cfDNA analysis. Here we reported a new targeted sequencing by combining single-strand library preparation and target capture (SLHC-seq). By applying the new technology in plasma cfDNA from pancreatic cancer patients, we achieved higher efficiency in analysis of mutations than previously reported using other detection assays. SLHC-seq rescued short or damaged cfDNA fragments along to increase the sensitivity and accuracy of circulating-tumor DNA detection. Most importantly, we found that the small mutant fragments are prevalent in early-stage patients, which provides strong evidence for fragment size-based early detection of pancreatic cancer. Collectively, the new pipeline enhanced our understanding of cfDNA biology and provide new insights for liquid biopsy.

cancer biology↗

bioRxiv2018

Inference of Differential Gene Regulatory Networks Based on Gene Expression and Genetic Perturbation Data

MotivationGene regulatory networks (GRNs) of the same organism can be different under different conditions, although the overall network structure may be similar. Understanding the difference in GRNs under different conditions is important to understand condition-specific gene regulation. When gene expression and other relevant data under two different conditions are available, they can be used by an existing network inference algorithm to estimate two GRNs separately, and then to identify the difference between the two GRNs. However, such an approach does not exploit the similarity in two GRNs, and may sacrifice inference accuracy.\n\nResultsIn this paper, we model GRNs with the structural equation model (SEM) that can integrate gene expression and genetic perturbation data, and develop an algorithm named fused sparse SEM (FSSEM), to jointly infer GRNs under two conditions, and then to identify difference of the two GRNs. Computer simulations demonstrate that the FSSEM algorithm outperforms the approach that estimates two GRNs separately. Analysis of a gene expression and SNP dataset of lung cancer and normal lung tissues with FSSEM inferred a GRN largely agree with the known lung GRN reported in the literature, and it identified a differential GRN, whose genes with largest degrees were reported to be implicated in lung cancer. The FSSEM algorithm provides a valuable tool for joint inference of two GRNs and identification of the differential GRN under two conditions.\n\nAvailabilityThe software package for the FSSEM algorithm is available at https://github.com/Ivis4ml/FSSEM.git\n\nContactx.cai@miami.edu

bioinformatics↗

bioRxiv2018

Efficient Proximal Gradient Algorithm for Inference of Differential Gene Networks

BackgroundGene networks in living cells can change depending on various conditions such as caused by different environments, tissue types, disease states, and development stages. Identifying the differential changes in gene networks is very important to understand molecular basis of various biological process. While existing algorithms can be used to infer two gene networks separately from gene expression data under two different conditions, and then to identify network changes, such an approach does not exploit the data jointly, and it is thus suboptimal. A desirable approach would be clearly to infer two gene networks jointly, which can yield improved estimates of network changes.\n\nResultsIn this paper, we developed a proximal gradient algorithm for differential network (ProGAdNet) inference, that jointly infers two gene networks under different conditions and then identifies changes in the network structure. Computer simulations demonstrated that our ProGAdNet outperformed existing algorithms in terms of inference accuracy, and was much faster than a similar approach for joint inference of gene networks. Gene expression data of breast tumors and normal tissues in the TCGA database were analyzed with our ProGAdNet, and revealed that 268 genes were involved in the changed network edges. Gene set enrichment analysis of this set of 268 genes identified a number of gene sets related to breast cancer or other types of cancer, which corroborated the gene set identified by ProGAdNet was very informative about the cancer disease status. A software package implementing the ProGAdNet and computer simulations is available upon request.\n\nConclusionWith its superior performance over existing algorithms, ProGAdNet provides a valuable tool for finding changes in gene networks, which may aid the discovery of gene-gene interactions changed under different conditions.

bioinformatics↗

bioRxiv2018

Structural and biochemical characterization on the cognate and heterologous interactions of the MazEF-mt9 TA system

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.

biochemistry↗