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Zhu, K.

Publications and source records attributed to Zhu, K..

At least 109 records · Page 6Linked to original sources

PI3K inhibition reverses migratory direction of single cells but not cell groups in electric field

Motile cells migrate directionally in the electric field in a process known as galvanotaxis. Galvanotaxis is important in wound healing, development, cell division, and nerve growth. Different cell types migrate in opposite directions in electric fields, to either cathode, or anode, and the same cell can switch the directionality depending on chemical conditions. We previously reported that individual fish keratocyte cells sense electric fields and migrate to the cathode, while inhibition of PI3K reverses single cells to the anode. Many physiological processes rely on collective, not individual, cell migration, so here we report on directional migration of cohesive cell groups in electric fields. Uninhibited cell groups of any size move to the cathode, with speed decreasing and directionality increasing with the group size. Surprisingly, large groups of PI3K-inhibited cells move to the cathode, in the direction opposite to that of individual cells, which move to the anode, while such small groups are not persistently directional. In the large groups, cells velocities are distributed unevenly: the fastest cells are at the front of the uninhibited groups, but at the middle and rear of the PI3K-inhibited groups. Our results are most consistent with the hypothesis, supported by the computational model, that cells inside and at the edge of the groups interpret directional signals differently. Namely, cells in the group interior are directed to the cathode independently of their chemical state. Meanwhile, edge cells behave like the individual cells: they are directed to the cathode/anode in uninhibited/PI3K-inhibited groups, respectively. As a result, all cells drive uninhibited groups to the cathode, but a mechanical tug-of-war between the inner and edge cells directs large PI3K-inhibited groups with cell majority in the interior to the cathode, while rendering small groups non-directional. Significance statementMotile cells migrate directionally in electric fields. This behavior - galvanotaxis - is important in many physiological phenomena. Individual fish keratocytes migrate to the cathode, while inhibition of PI3K reverses single cells to the anode. Uninhibited cell groups move to the cathode. Surprisingly, large groups of PI3K-inhibited cells also move to the cathode, in the direction opposite to that of individual cells. The fastest cells are at the front of the uninhibited groups, but at the middle and rear of the PI3K-inhibited groups. We posit that inner and edge cells interpret directional signals differently, and that a tug-of-war between the edge and inner cells directs the cell groups. These results shed light on general principles of collective cell migration.

biophysics↗

A chromosome-level genome assembly of the yellowfin seabream (Acanthopagrus latus) (Hottuyn, 1782) provides insights into its osmoregulation and sex reversal

The yellowfin seabream Acanthopagrus latus is the economically most important Sparidae fish species in the northern South China Sea. As euryhaline fish, they are perfect model for investigating osmoregulatory mechanisms in teleosts. Moreover, the reproductive biology of hermaphrodites has long been intriguing; however, very little is known about the molecular pathways underlying their sex change. To elucidate genetic mechanisms of osmoregulation and sex reversal in this fish, a high-quality reference genome of the yellowfin seabream was generated by a combination of Illumina and PacBio technologies. The draft genome of yellowfin seabream was 806 Mb, with 732 Mb scaffolds anchored on 24 chromosomes. The contig N50 and scaffold N50 were 2.6 Mb and 30.17 Mb, respectively. The assembly is of high integrity and includes 92.23% universal single-copy orthologues based on benchmarking universal single-copy orthologs (BUSCO) analysis. Moreover, among the 19,631 protein-coding genes, we found that the ARRDC3 and GSTA gene families related to osmoregulation underwent an extensive expansion in two euryhaline Sparidae fish genomes compared to other teleost genomes. Moreover, integrating sex-specific transcriptome analyses, several genes related to the transforming growth factor beta (TGF-{beta}) signalling pathway involved in sex differentiation and development. This genomic resource will not only be valuable for studying the osmoregulatory mechanisms in estuarine fish and sex determination in hermaphrodite vertebrate species, but also provide useful genomic tools for facilitating breeding of the yellowfin seabream.

genomics↗

Single-cell RNA-seq analysis reveals the pan-cancer transformation of adipose-derived stromal cells into COL11A1-expressing metastasis associated fibroblasts

During the last ten years, many research results have been referring to a particular type of cancer-associated fibroblasts associated with poor prognosis, invasiveness, metastasis and resistance to therapy in multiple cancer types, characterized by a gene expression signature with prominent presence of genes COL11A1, THBS2 and INHBA. Identifying the underlying biological mechanisms responsible for their creation may facilitate the discovery of targets for potential pan-cancer therapeutics. Using a novel computational approach for single-cell gene expression data analysis identifying the dominant cell populations in a sequence of samples from patients at various stages, we conclude that these fibroblasts are produced by a pan-cancer cellular transition originating from a particular type of adipose-derived stromal cells naturally present in the stromal vascular fraction of normal adipose tissue, having a characteristic gene expression signature. Focusing on a rich pancreatic cancer dataset, we provide a detailed description of the continuous modification of the gene expression profiles of cells as they transition from APOD-expressing adipose-derived stromal cells to COL11A1-expressing cancer-associated fibroblasts, identifying the key genes that participate in this transition. These results also provide an explanation to the well-known fact that the adipose microenvironment contributes to cancer progression. Author summaryComputational analysis of rich gene expression data at the single-cell level from cancer biopsies can lead to biological discoveries about the nature of the disease. Using a computational methodology that identifies the gene expression profile of the dominant cell population for a particular cell type in the microenvironment of tumors, we observed that there is a remarkably continuous modification of this profile among patients, corresponding to a cellular transition. Specifically, we found that the starting point of this transition has a unique characteristic signature corresponding to cells that are naturally residing in normal adipose tissue. We also found that the endpoint of the transition has another characteristic signature corresponding to a particular type of cancer-associated fibroblasts with prominent expression of gene COL11A1, which has been found strongly associated with invasiveness, metastasis and resistance to therapy in multiple cancer types. Our results provide an explanation to the well-known fact that the adipose tissue contributes to cancer progression, shedding light on the biological mechanism by which tumor cells interact with the adipose microenvironment. We provide a detailed description of the changing profile during the transition, identifying associated genes as potential targets for pan-cancer therapeutics inhibiting the underlying mechanism.

cancer biology↗

Combinatorial Algorithms for Strain Level Metagenomic Microbial Detection and Quantification

The identification and quantification of microbial abundance at the species or strain level from sequencing data is crucial for our understanding of human health and disease. Existing approaches for microbial abundance estimation either use accurate but computationally expensive alignment-based approaches for species-level estimation or less accurate but computationally fast alignment-free approaches that fail to classify many reads accurately at the species or strain-level. Here we introduce CAMMiQ, a novel combinatorial solution to the microbial identification and abundance estimation problem, which performs better than the best used tools on simulated and real datasets with respect to the number of correctly classified reads (i.e., specificity) by an order of magnitude and resolves possible mixtures of similar genomes. As we demonstrate, CAMMiQ can better distinguish between single cells deliberately infected with distinct Salmonella strains and sequenced using scRNA-seq reads than alternative approaches. We also demonstrate that CAMMiQ is also more accurate than the best used approaches on a variety of synthetic genomic read data involving some of the most challenging bacterial genomes derived from NCBI RefSeq database; it can distinguish not only distinct species but also closely related strains of bacteria. The key methodological innovation of CAMMiQ is its use of arbitrary length, doubly-unique substrings, i.e. substrings that appear in (exactly) two genomes in the input database, instead of fixed-length, unique substrings. To resolve the ambiguity in the genomic origin of doubly-unique substrings, CAMMiQ employs a combinatorial optimization formulation, which can be solved surprisingly quickly. CAMMiQs index consists of a sparsified subset of the shortest unique and doubly-unique substrings of each genome in the database, within a user specified length range and as such it is fairly compact. In short, CAMMiQ offers more accurate genomic identification and abundance estimation than the best used alternatives while using similar computational resources. Availabilityhttps://github.com/algo-cancer/CAMMiQ

bioinformatics↗

Single Cell-type Integrative Network Modeling IdentifiedNovel Microglial-specific Targets for the Phagosome inAlzheimer's disease

SummaryLate-Onset Alzheimer’s Disease (LOAD) results from a complex pathological process influenced by genetic variation, aging and environment factors. Genetic susceptibility factors indicate that myeloid cells such as microglia play a significant role in the onset of LOAD. Here, we developed a computational systems biology approach to construct probabilistic causal and predictive network models of genetic regulatory programs of microglial cells under LOAD diagnosis by integrating two independent brain transcriptome and genome-wide genotype datasets from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MAYO) studies in the AMP-AD consortium. From this network model, we identified and replicated novel microglial-specific master regulators predicted to modulate network states associated with LOAD. We experimentally validated three microglial master regulators (FCER1G, HCK and LAPTM5) in primary human microglia-like cells (MDMi) by demonstrating the molecular impact these master regulators have on modulating downstream genomic targets identified by our top-down/bottom-up method and the causal relations among the three key drivers. These master regulators are involved in phagocytosis, a process associated with LOAD. Thus, we propose three new master regulator (key driver) genes that emerged from our network analyses as robust candidates for further evaluation in LOAD therapeutic development efforts.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

ORN: Extracting Latent Pathway Activities in Cancer with OR-gate Network

Pathway level understanding of cancer plays a key role in precision oncology. In this study, we developed a novel data-driven model, called the OR-gate Network (ORN), to simultaneously infer functional relationships among mutations, patient-specific pathway activities, and gene co-expression. In principle, logical OR gates agree with mutual exclusivity patterns in somatic mutations and bicluster patterns in transcriptomic profiles. In a trained ORN, the differential expression profiles of tumours can be explained by somatic mutations perturbing signalling pathways. We applied ORN to lower grade glioma (LLG) samples in TCGA and breast cancer samples from METABRIC. Both datasets have shown pathway patterns related to immune response and cell cycles. In LLG samples, ORN identified multiple metabolic pathways closely related to glioma development and revealed two pathways closely related to patient survival. Additional results from the METABRIC datasets showed that ORN could characterize key mechanisms of cancer and connect them to less studied somatic mutations (e.g., BAP1, MIR604, MICAL3, and telomere activities), which may generate novel hypothesis for targeted therapy.

bioinformatics↗

Gsta4 controls apoptosis of differentiating adult oligodendrocytes during homeostasis and remyelination via the mitochondria-associated Fas/Casp8/Bid-axis

Arrest of oligodendrocyte (OL) differentiation and remyelination following myelin damage in Multiple Sclerosis (MS) are associated with disease progression but the underlying mechanism are elusive. We show that Glutathione S-transferase 4 (Gsta4) is highly expressed during adult OL differentiation and that its loss prevents differentiation into myelinating OLs. Also, Gsta4 appeared to be a novel target for Clemastine, in clinical trial for MS. Over-expression of Gsta4 reduced the expression of Fas and activity along the mitochondria-associated Casp8/Bid-axis in adult pre-OLs from the corpus callosum, together promoting enhanced pre-OL survival during differentiation. The Gsta4-mediated input on apoptosis during adult OL differentiation was further verified in the LPC and EAE model, where Casp8 were reduced in pre-OLs with high Gsta4 expression in an immune response-independent fashion. Our results place Gsta4 as a key regulator of intrinsic mechanisms beneficial for OL differentiation and remyelination, and as a possible target for future MS therapies.

neuroscience↗

Montane species and communities track recent warming more closely in the tropics

Many species are responding to global warming by shifting their distributions upslope to higher elevations, but the observed rates of shifts vary considerably among studies. Here we test the hypothesis that this variation is in part explained by latitude, with tropical species being generally more responsive to warming temperatures than are temperate species. We find support for this hypothesis in each of two independent empirical datasets--shifts in species elevational ranges, and changes in composition of forest inventory tree plots. Tropical species are tracking rising temperatures 2.1-2.4 times (range shift dataset) and 10 times (tree plot dataset) better than their temperate counterparts. Models predict that for a 100 m upslope shift in temperature isotherm, species at the equator have shifted their elevational ranges 93-96 m upslope, while species at 45{degrees} latitude have shifted only 37-42 m upslope. For tree plots, models predict that a 1{degrees}C increase in temperature leads to an increase in community temperature index (CTI), a metric of the average temperature optima of tree species within a plot, of 0.56 {degrees}C at the equator but no change in CTI at 45{degrees} latitude (-0.033). This latitudinal gradient in temperature tracking suggests that tropical montane biotas may be on an "escalator to extinction" as global temperatures continue to rise.

ecology↗

Axonal mitochondria across species adjust in diameter depending on thickness of surrounding myelin

In the central nervous system (CNS), axons and its surrounding myelin sheaths, generated by oligodendrocytes, greatly depend on each other, where oligodendrocytes provide axons with both trophic and metabolic support. Across spices, assessment of the axon-myelin ultrastructure is the key-approach to visualize de- and re-myelination of axons. However, this assessment omits to provide information on axonal homeostasis or how axon-myelin influence one another. Since mitochondria may adjust in size thus mirroring the intracellular physiological and metabolic status we applied this to myelinated axons in the CNS. We herein show that a large axonal mitochondria diameter correlates with thinner surrounding myelin sheaths across different CNS tracts and species, including human. We also show that the relation between axonal mitochondria diameter and surrounding myelin thickness is a valuable measurement to verify advanced remyelination in two commonly used experimental demyelinating models, namely the cuprizone and the lysolecithin (LPC) model. Lastly, we show that axonal mitochondria adjust in diameter in response to the thickness of the axonal surrounding myelin whereas the opposite adaption was absent. In summary, the link between axonal mitochondria diameter and surrounding myelin thickness provide insight on the axon-myelin relation both during homeostasis and pathological conditions. This link is also translational applicable and can thus contribute to a better understanding on how to study remyelination using experimental models.

neuroscience↗

A Novel Droplet Digital PCR Human mtDNA Assay for Global Fecal Source Tracking

Human mitochondrial DNA (mtDNA) provides a promising target for microbial source tracking because it is unique to humans and universal across human individuals. We developed a droplet digital PCR (ddPCR) assay, hCYTB484, targeting the cytochrome b gene of the human mtDNA and compared the performance of the hCYTB484 assay with a widely used assay targeting human-associated Bacteroides, the HF183/BacR287 assay. We also defined and validated the analytical limit of detection and analytical lower limit of quantification; these analytical limits determine the concentration levels above which samples are declared to be positive and quantifiable for the target, respectively. We found both assays to be highly specific (95%) against cow and pig feces; however, the hCYTB484 was more sensitive when tested against individual human feces from US, Bangladesh, and Mozambique (100% versus a mean of 51% across the 3 countries). To further compare the performance of the two assays, we utilized a receiver operating characteristic curve, showing that the hCYTB484 marker was widely distributed across human feces from the 3 different geographical regions tested and in higher quantities than the HF183/BacR287 marker. The higher performance of the hCYTB484 marker in individual feces is a desirable characteristic in the detection of fecal pollution from sources to which fewer individuals contribute, such as non-sewered types of sanitation that serve most of Earths population and carry the highest risk of exposure to fecal-oral pathogens.\n\nImportanceThe usefulness of an ideal human-specific, culture- and library-independent marker to the microbial source tracking field is reflected by the numerous efforts to develop such markers; however, thus far, microbial-based markers of this type have exhibited variable source-specificity across geographies and variable sensitivity across scales of fecal waste. Most of the worlds population is served by non-sewered forms of sanitation that also carry the highest risk of exposure to fecal-oral pathogens. This reality underscores the need for markers of human fecal contamination that have high sensitivity in fecal pollution sources to which fewer individuals contribute to, such as fecal sludges found in pit latrines. We show that human mtDNA-based methods can be highly source-specific and highly sensitive in smaller scales of fecal pollution, providing a useful addition to the microbial source tracking toolbox by complementing the variable performance of microbial-based markers.

microbiology↗

Comparative genomic analysis of the pheromone receptor Class 1 family (V1R) reveals extreme complexity in mouse lemurs (genus, Microcebus) and chromosomal hotspots across mammals

Sensory gene families are of special interest, both for what they can tell us about molecular evolution, and for what they imply as mediators of social communication. The vomeronasal type-1 receptors (V1Rs) have often been hypothesized as playing a fundamental role in driving or maintaining species boundaries given their likely function as mediators of intraspecific mate choice, particularly in nocturnal mammals. Here, we employ a comparative genomic approach for revealing patterns of V1R evolution within primates, with a special focus on the small-bodied nocturnal mouse and dwarf lemurs of Madagascar (genera Microcebus and Cheirogaleus, respectively). By doubling the existing genomic resources for strepsirrhine primates (i.e., the lemurs and lorises), we find that the highly-speciose and morphologically-cryptic mouse lemurs have experienced an elaborate proliferation of V1Rs that we argue is functionally related to their capacity for rapid lineage diversification. Contrary to a previous study that found equivalent degrees of V1R diversity in diurnal and nocturnal lemurs, our study finds a strong correlation between nocturnality and V1R elaboration, with nocturnal lemurs showing elaborate V1R repertoires and diurnal lemurs showing less diverse repertoires. Recognized subfamilies among V1Rs show unique signatures of diversifying positive selection, as might be expected if they have each evolved to respond to specific stimuli. Further, a detailed syntenic comparison of mouse lemurs with mouse (genus Mus) and other mammalian outgroups shows that orthologous mammalian subfamilies, predicted to be of ancient origin, tend to cluster in a densely populated region across syntenic chromosomes that we refer to as V1R \"hotspots.\"

genomics↗

Patterning of the vertebrate head in time and space by BMP signalling

How head patterning is regulated in vertebrates is yet to be understood. In this study, we show that frog embryos injected with Noggin at different blastula and gastrula stages had their head development sequentially arrested at different positions. When timed BMP inhibition was applied to BMP-overexpressing embryos, the expression of five genes: xcg-1 (a marker of the cement gland, which is the front-most structure in the frog embryo), six3 (a forebrain marker), otx2 (a forebrain and mid-brain marker), gbx2 (an anterior hindbrain marker) and hoxd1 (a posterior hindbrain marker) were sequentially fixed. These results suggest that timed interactions between BMP and anti-BMP are involved in patterning the vertebrate head progressively in time and space. Since the above genes are not expressed sequentially, there may be a BMP dependent gene sequence during head patterning that can be arrested by BMP inhibition and regulate the specification of positional values in the head.

developmental biology↗

Mechanosensing by the lamina protects against nuclear rupture, DNA damage, and cell cycle arrest

Whether cell forces or extracellular matrix (ECM) can impact genome integrity is largely unclear. Here, acute perturbations (~1hr) to actomyosin stress or ECM elasticity cause rapid and reversible changes in lamin-A, DNA damage, and cell cycle. Embryonic hearts, differentiated iPS-cells, and various nonmuscle cell types all show that actomyosin-driven nuclear rupture causes cytoplasmic mis-localization of DNA repair factors and excess DNA damage. Binucleation and micronuclei increase as telomeres shorten, which all favor cell cycle arrest. Deficiencies in lamin-A and repair factors exacerbate these effects, but lamin-A-associated defects are rescued by repair factor overexpression and by contractility modulators in clinical trials. Contractile cells on stiff ECM normally exhibit low phosphorylation and slow degradation of lamin-A by matrix-metalloprotease-2 (MMP2), and inhibition of this lamin-A turnover and also actomyosin contractility is seen to minimize DNA damage. Lamin-A is thus stress-stabilized to mechano-protect the genome.

cell biology↗

Positive feedback loop of regulating ERK phosphorylation in mESCs mediated by Etv5-Tet2-Fgfr2 axis

Dynamic equilibrium of extracellular signal-regulated kinase (ERK) activity is regulated elaborately by multiple feedback loops to ensure the normal self-renewal of mouse embryonic stem cells (mESCs). Previous studies on mESCs have demonstrated that the negative feedback loops are engaged to prevent the overactivated ERK phosphorylation (pERK). It is not clear whether there is any positive feedback loop involved to maintain a minimum of pERK in mESCs. Here, we found that blocking fibroblast growth factor (FGF)-ERK pathway by chemical PD0325901 downregulated the transcription of E26 transformation-specific (ETS) family transcription factor Etv5 in mESCs. In turn, knockout (KO) of Etv5 by CRISPR/Cas9 decreased pERK. Moreover, Etv5 KO enhanced the DNA methylation at promoter of fibroblast growth factor receptor 2 (Fgfr2) by downregulating DNA hydroxylase Tet2, which further decreased the expression of Fgfr2 in mESCs. Collectively, a positive feedback loop of regulating pERK was revealed in mESCs, which was mediated by Etv5-Tet2-Fgfr2 axis. Our findings provide a new paradigm for pERK regulation in mESCs and will be useful to understand the cell fate determination during early embryo development.

developmental biology↗

Live cell monitoring for factors affecting genome variation

Cancer cells and pluripotent stem cells frequently exhibit gains or losses of entire chromosomes and chromosome segments, and the typical terminal analyses of genomes suggest this aneuploidy is ongoing and particularly variable in solid tumors. Here, we quantify aneuploidy-inducing perturbations by live cell fluorescence monitoring for changes in chromosome-5 in a lung cancer line and in normal diploid iPS cells. Inhibition of the spindle assembly checkpoint (SAC) and knockdown of DNA repair factors cause chromosome mis-segregation to increase several-fold above a low baseline level, and both perturbations also generate several-fold more rare fluorescent-null cells. Loss of chromosome-5 is confirmed by single cell karyotyping, SNP arrays on stable isolated clones, and downregulated expression of genes on chromosome-5 in single cell transcriptomics. The iPS cells also show loss of fluorescence in infrequent cells after SAC inhibition and upon growth as teratomas in mice. Viability, selection, and altered expression can thus be tracked to reveal molecular mechanisms in aneuploidy.

genomics↗

Rescue of DNA damage in cells after constricted migration reveals bimodal mechano-regulation of cell cycle

Migration through constrictions can clearly rupture nuclei and mis-localize nuclear proteins but damage to DNA remains uncertain as does any effect on cell cycle. Here, myosin-II inhibition rescues rupture and partially rescues the DNA damage marker {gamma}H2AX, but an apparent delay in cell cycle is unaffected. Co-overexpression of multiple DNA repair factors and antioxidant inhibition of break formation also have partial effects, independent of rupture. However, there seems to be a bimodal dependence of cell cycle on DNA damage. Migration through custom-etched pores yields the same bimodal, with ~4-m pores causing intermediate levels of damage and cell cycle delay. Micronuclei (generated in faulty division) of the smallest diameter appear similar to ruptured nuclei, with high DNA damage and entry of chromatin-binding cGAS (cyclic-GMP-AMP-synthase) from cytoplasm but low repair factor levels. Increased genomic variation after constricted migration is quantified in expanding clones and is consistent with (mis)repair of excess DNA damage and subsequent proliferation.

cell biology↗

Sketching Algorithms for Genomic Data Analysis and Querying in a Secure Enclave

Current practices in collaborative genomic data analysis (e.g. PCAWG [1]) necessitate all involved parties to exchange individual patient data and perform all analysis locally, or use a trusted server for maintaining all data to perform analysis in a single site (e.g. the Cancer Genome Collaboratory). Since both approaches involve sharing genomic sequence data - which is typically not feasible due to privacy issues, collaborative data analysis remains to be a rarity in genomic medicine.\n\nIn order to facilitate efficient and effective collaborative or remote genomic computation we introduce SkSES (Sketching algorithms for Secure Enclave based genomic data analysiS), a computational framework for performing data analysis and querying on multiple, individually encrypted genomes from several institutions in an untrusted cloud environment. Unlike other techniques for secure/privacy preserving genomic data analysis, which typically rely on sophisticated cryptographic techniques with prohibitively large computational overheads, SkSES utilizes the secure enclaves supported by current generation microprocessor architectures such as Intels SGX. The key conceptual contribution of SkSES is its use of sketching data structures that can fit in the limited memory available in a secure enclave.\n\nWhile streaming/sketching algorithms have been developed for many applications in computer science, their feasibility in genomics has remained largely unexplored. On the other hand, even though privacy and security issues are becoming critical in genomic medicine, available cryptographic techniques based on, e.g. homomorphic encryption or garbled circuits, fail to address the performance demands of this rapidly growing field. The alternative offered by Intels SGX, a combination of hardware and software solutions for secure data analysis, is severely limited by the relatively small size of a secure enclave, a private region of the memory protected from other processes. SkSES addresses this limitation through the use of sketching data structures to support efficient secure and privacy preserving SNP analysis across individually encrypted VCF files from multiple institutions. In particular SkSES provides the users the ability to query for the \"k most significant SNPs\" among any set of user specified SNPs and any value of k - even when the total number of SNPs to be maintained is far beyond the memory capacity of the secure enclave.\n\nResultsWe tested SkSES on the complete iDASH-2017 competition data set comprised of 1000 case and 1000 control samples related to an unknown phenotype. SkSES was able to identify the top SNPs with respect to the{chi} 2 statistic, among any user specified subset of SNPs across this data set of 2000 individually encrypted complete human genomes quickly and accurately - demonstrating the feasibility of secure and privacy preserving computation for genomic medicine via Intels SGX.\n\nAvailabilityhttps://github.com/ndokmai/sgx-genome-variants-search

bioinformatics↗

Universal antibiotic tolerance arising from antibiotic-triggered accumulation of redox metabolites

Pseudomonas aeruginosa is an opportunistic pathogen that often infects open wounds or patients with cystic fibrosis. Once established, P. aeruginosa infections are notoriously difficult to eradicate. This difficulty is in part due to the ability of P. aeruginosa to tolerate antibiotic treatment at the individual-cell level or through collective behaviors. Here we describe a new mechanism by which P. aeruginosa tolerates antibiotic treatment by modulating its global cellular metabolism. In particular, treatment of P. aeruginosa with sublethal concentrations of antibiotics covering all major classes promoted accumulation of the redox-sensitive phenazine - pyocyanin (PYO). PYO in turn conferred general tolerance against diverse antibiotics for both P. aeruginosa and other Gram-negative and Gram-positive bacteria. We show that PYO promotes energy generation to enhance the activity of efflux pumps, leading to enhanced antibiotic tolerance. This property is shared by other redox-active phenazines produced by P. aeruginosa. Our discovery sheds new insights into the physiological functions of phenazines and has implications for designing effective antibiotic treatment protocols.\n\nAuthor SummaryAntibiotic tolerance can facilitate the evolution of resistance, and here we describe a previously unknown mechanism of collective antibiotic tolerance in Pseudomonas aeruginosa. In particular, P. aeruginosa treated with sublethal concentrations of antibiotics covering all major classes promotes accumulation of pyocyanin (PYO), an important virulence factor. In turn, PYO confers general tolerance against diverse antibiotics for both P. aeruginosa and other bacteria. Our discovery is a perfect example of what Nietzsche once said: That which does not kill me makes me stronger.

microbiology↗