N6-methyladenosine-driven miR-143/145-KLF4 circuit orchestrates the phenotypic switch of pulmonary artery smooth muscle cells.

Pulmonary hypertension (PH) is characterized by vascular remodeling predominantly driven by a phenotypic switching in pulmonary artery smooth muscle cells (PASMCs). However, the underlying mechanisms for this phenotypic alteration remain incompletely understood. Here, we identified that RNA methyltransferase METTL3 is significantly elevated in the lungs of hypoxic PH (HPH) mice and rats, as well as in the pulmonary arteries (PAs) of HPH rats. Targeted deletion of Mettl3 in smooth muscle cells exacerbated hemodynamic consequences of hypoxia-induced PH and accelerated pulmonary vascular remodeling in vivo. Additionally, the absence of METTL3 markedly induced phenotypic switching in PASMCs in vitro. Mechanistically, METTL3 depletion attenuated m6A modification and hindered the processing of pri-miR-143/145, leading to a downregulation of miR-143-3p and miR-145-5p. Inhibition of hnRNPA2B1, an m6A mediator involved in miRNA maturation, similarly resulted in a significant reduction of miR-143-3p and miR-145-5p. We demonstrated that miR-145-5p targets Krüppel-like factor 4 (KLF4) and miR-143-3p targets fascin actin-bundling protein 1 (FSCN1) in PASMCs. The decrease of miR-145-5p subsequently induced an upregulation of KLF4, which in turn suppressed miR-143/145 transcription, establishing a positive feedback circuit between KLF4 and miR-143/145. This regulatory circuit facilitates the persistent suppression of contractile marker genes, thereby sustaining PASMC phenotypic switch. Collectively, hypoxia-induced upregulation of METTL3, along with m6A mediated regulation of miR-143/145, might serve as a protective mechanism against phenotypic switch of PASMCs. Our results highlight a potential therapeutic strategy targeting m6A modified miR-143/145-KLF4 loop in the treatment of PH.

Modular Synthesis of Phthalaldehyde Derivatives Enabling Access to Photoacid Generator-Bound Self-Immolative Polymer Resists with Next-Generation Photolithographic Properties.

The resolution, line edge roughness, and sensitivity (RLS) trade-off has fundamentally limited the lithographic performance of chemically amplified resists. Production of next-generation transistors using extreme ultraviolet (EUV) lithography depends on a solution to this problem. A resist that simultaneously increases the effective reaction radius of its photogenerated acids while limiting their diffusion radius should provide an elegant solution to the RLS barrier. Here, we describe a generalized synthetic approach to phthalaldehyde derivatives using sulfur(VI) fluoride exchange click chemistry that dramatically expands usable chemical space by enabling virtually any non-ionic photoacid generator (PAG) to be tethered to phthalaldehyde. The resulting polymers represent the first ever PAG-tethered self-immolative resists in an architecture that simultaneously displays high contrast, extraordinary sensitivity, and low roughness under EUV exposure. We believe this class of resists will ultimately enable researchers to overcome the RLS trade-off.

Alternating Copolymerization of CO2 and Cyclohexene Oxide Catalyzed by Cobalt-Lanthanide Mixed Multinuclear Complexes.

Heteromultimetallic complexes consisting of three Co(II) ions and one lanthanide ion were synthesized and applied to the alternating copolymerization of CO2 and cyclohexene oxide. Unlike the conventional cobalt(III) salen complexes, the high thermal stability of the present catalyst allowed us to reach a turnover number of 13000, one of the highest values ever reported for multimetallic systems. The chain propagation was first-order to the catalyst, suggesting a cooperative behavior of the metal centers.

A novel essential domain perspective for exploring gene essentiality.

MOTIVATION: Genes with indispensable functions are identified as essential; however, the traditional gene-level studies of essentiality have several limitations. In this study, we characterized gene essentiality from a new perspective of protein domains, the independent structural or functional units of a polypeptide chain. RESULTS: To identify such essential domains, we have developed an Expectation-Maximization (EM) algorithm-based Essential Domain Prediction (EDP) Model. With simulated datasets, the model provided convergent results given different initial values and offered accurate predictions even with noise. We then applied the EDP model to six microbial species and predicted 1879 domains to be essential in at least one species, ranging 10-23% in each species. The predicted essential domains were more conserved than either non-essential domains or essential genes. Comparing essential domains in prokaryotes and eukaryotes revealed an evolutionary distance consistent with that inferred from ribosomal RNA. When utilizing these essential domains to reproduce the annotation of essential genes, we received accurate results that suggest protein domains are more basic units for the essentiality of genes. Furthermore, we presented several examples to illustrate how the combination of essential and non-essential domains can lead to genes with divergent essentiality. In summary, we have described the first systematic analysis on gene essentiality on the level of domains. CONTACT: huilu.bioinfo@gmail.com or Long.Lu@cchmc.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Network-Based Analysis on Orthogonal Separation of Human Plasma Uncovers Distinct High Density Lipoprotein Complexes.

High density lipoprotein (HDL) particles are blood-borne complexes whose plasma levels have been associated with protection from cardiovascular disease (CVD). Recent studies have demonstrated the existence of distinct HDL subspecies; however, these have been difficult to isolate and characterize biochemically. Here, we present the first report that employs a network-based approach to systematically infer HDL subspecies. Healthy human plasma was separated into 58 fractions using our previously published three orthogonal chromatography techniques. Similar local migration patterns among HDL proteins were captured with a novel similarity score, and individual comigration networks were constructed for each fraction. By employing a graph mining algorithm, we identified 183 overlapped cliques, among which 38 were further selected as candidate HDL subparticles. Each of these 38 subparticles had at least two literature supports. In addition, GO function enrichment analysis showed that they were enriched with fundamental biological and CVD protective functions. Furthermore, gene knockout experiments in mouse model supported the validity of these subparticles related to three apolipoproteins. Finally, analysis of an apoA-I deficient human patient's plasma provided additional support for apoA-I related complexes. Further biochemical characterization of these putative subspecies may facilitate the mechanistic research of CVD and guide targeted therapeutics aimed at its mitigation.

Multi-dimensional co-separation analysis reveals protein-protein interactions defining plasma lipoprotein subspecies.

The distribution of circulating lipoprotein particles affects the risk for cardiovascular disease (CVD) in humans. Lipoproteins are historically defined by their density, with low-density lipoproteins positively and high-density lipoproteins (HDLs) negatively associated with CVD risk in large populations. However, these broad definitions tend to obscure the remarkable heterogeneity within each class. Evidence indicates that each class is composed of physically (size, density, charge) and compositionally (protein and lipid) distinct subclasses exhibiting unique functionalities and differing effects on disease. HDLs in particular contain upward of 85 proteins of widely varying function that are differentially distributed across a broad range of particle diameters. We hypothesized that the plasma lipoproteins, particularly HDL, represent a continuum of phospholipid platforms that facilitate specific protein-protein interactions. To test this idea, we separated normal human plasma using three techniques that exploit different lipoprotein physicochemical properties (gel filtration chromatography, ionic exchange chromatography, and preparative isoelectric focusing). We then tracked the co-separation of 76 lipid-associated proteins via mass spectrometry and applied a summed correlation analysis to identify protein pairs that may co-reside on individual lipoproteins. The analysis produced 2701 pairing scores, with the top hits representing previously known protein-protein interactions as well as numerous unknown pairings. A network analysis revealed clusters of proteins with related functions, particularly lipid transport and complement regulation. The specific co-separation of protein pairs or clusters suggests the existence of stable lipoprotein subspecies that may carry out distinct functions. Further characterization of the composition and function of these subspecies may point to better targeted therapeutics aimed at CVD or other diseases.

miR-21 attenuates lipopolysaccharide-induced lipid accumulation and inflammatory response: potential role in cerebrovascular disease.

BACKGROUND: Atherosclerosis constitutes the leading contributor to morbidity and mortality in cardiovascular and cerebrovascular diseases. Lipid deposition and inflammatory response are the crucial triggers for the development of atherosclerosis. Recently, microRNAs (miRNAs) have drawn more attention due to their prominent function on inflammatory process and lipid accumulation in cardiovascular and cerebrovascular disease. Here, we investigated the involvement of miR-21 in lipopolysaccharide (LPS)-induced lipid accumulation and inflammatory response in macrophages. METHODS: After stimulation with the indicated times and doses of LPS, miR-21 mRNA levels were analyzed by Quantitative real-time PCR. Following transfection with miR-21 or anti-miR-21 inhibitor, lipid deposition and foam cell formation was detected by high-performance liquid chromatography (HPLC) and Oil-red O staining. Furthermore, the inflammatory cytokines interleukin 6 (IL-6) and interleukin 10 (IL-10) were evaluated by Enzyme-linked immunosorbent assay (ELISA) assay. The underlying molecular mechanism was also investigated. RESULTS: In this study, LPS induced miR-21 expression in macrophages in a time- and dose-dependent manner. Further analysis confirmed that overexpression of miR-21 by transfection with miR-21 mimics notably attenuated lipid accumulation and lipid-laden foam cell formation in LPS-stimulated macrophages, which was reversely up-regulated when silencing miR-21 expression via anti-miR-21 inhibitor transfection, indicating a reverse regulator of miR-21 in LPS-induced foam cell formation. Further mechanism assays suggested that miR-21 regulated lipid accumulation by Toll-like receptor 4 (TLR4) and nuclear factor-κB (NF-κB) pathway as pretreatment with anti-TLR4 antibody or a specific inhibitor of NF-κB (PDTC) strikingly dampened miR-21 silence-induced lipid deposition. Additionally, overexpression of miR-21 significantly abrogated the inflammatory cytokines secretion of IL-6 and increased IL-10 levels, the corresponding changes were also observed when silencing miR-21 expression, which was impeded by preconditioning with TLR4 antibody or PDTC. CONCLUSIONS: Taken together, these results corroborated that miR-21 could negatively regulate LPS-induced lipid accumulation and inflammatory responses in macrophages by the TLR4-NF-κB pathway. Accordingly, our research will provide a prominent insight into how miR-21 reversely abrogates bacterial infection-induced pathological processes of atherosclerosis, indicating a promising therapeutic prospect for the prevention and treatment of atherosclerosis by miR-21 overexpression.

BMP4 enhances foam cell formation by BMPR-2/Smad1/5/8 signaling.

Atherosclerosis and its complications are characterized by lipid-laden foam cell formation. Recently, an obvious up-regulation of BMP4 was observed in atherosclerotic plaque, however, its function and the underlying mechanism remains unknown. In our study, BMP4 pretreatment induced macrophage foam cell formation. Furthermore, a dramatic increase in the ratio of cholesteryl ester (CE) to total cholesterol (TC) was observed in BMP4-treated macrophages, accompanied by the reduction of cholesterol outflow. Importantly, BMP4 stimulation inhibited the expression levels of the two most important cellular cholesterol transporters ABCA1 and ABCG1, indicating that BMP4 may induce formation of foam cells by attenuating transporters expression. Further mechanism analysis showed that BMPR-2, one of the BMP4 receptors, was significantly increased in BMP4 treated macrophage foam cells. That blocking its expression using specific siRNA significantly increased ABCA1 and ABCG1 levels. Additionally, BMP4 treatment triggered the activation of Smad1/5/8 pathway by BMPR-2 signaling. After blocking the Smad1/5/8 with its inhibitor, ABCA1 and ABCG1 expression levels were up-regulated significantly, suggesting that BMP4 inhibited the expression of ABCA1 and ABCG1 through the BMPR-2/Smad1/2/8 signaling pathway. Therefore, our results will provide a new insight about how BMP4 accelerate the progressio of atherosclerosis, and it may become a potential target against atherosclerosis and its complications.

A Drosophila model of the neurodegenerative disease SCA17 reveals a role of RBP-J/Su(H) in modulating the pathological outcome.

Expanded polyglutamine (polyQ) tract in the human TATA-box-binding protein (hTBP) causes the neurodegenerative disease spinocerebellar ataxia 17 (SCA17). To investigate the pathological effects of polyQ expansion, we established a SCA17 model in Drosophila. Similar to SCA17 patients, transgenic flies expressing a mutant hTBP protein with an expanded polyQ tract (hTBP80Q) exhibit progressive neurodegeneration, late-onset locomotor impairment and shortened lifespan. Microarray analysis reveals that hTBP80Q causes widespread and time-dependent transcriptional dysregulation in Drosophila. In a candidate screen for genetic modifiers, we identified RBP-J/Su(H), a transcription factor that contains Q/N-rich domains and participates in Notch signaling. Knockdown of Su(H) by RNAi further enhances hTBP80Q-induced eye defects, whereas overexpression of Su(H) suppresses such defects. While the Su(H) transcript level is not significantly altered in hTBP80Q-expressing flies, genes that contain Su(H)-binding sites are among those that are dysregulated. We further show that hTBP80Q interacts more efficiently with Su(H) than wild-type hTBP, suggesting that a reduction in the fraction of Su(H) available for its normal cellular functions contributes to hTBP80Q-induced phenotypes. While the Notch signaling pathway has been implicated in several neurological disorders, our study suggests a possibility that the activity of its nuclear component RBP-J/Su(H) may modulate the pathological progression in SCA17 patients.

Investigating the predictability of essential genes across distantly related organisms using an integrative approach.

Rapid and accurate identification of new essential genes in under-studied microorganisms will significantly improve our understanding of how a cell works and the ability to re-engineer microorganisms. However, predicting essential genes across distantly related organisms remains a challenge. Here, we present a machine learning-based integrative approach that reliably transfers essential gene annotations between distantly related bacteria. We focused on four bacterial species that have well-characterized essential genes, and tested the transferability between three pairs among them. For each pair, we trained our classifier to learn traits associated with essential genes in one organism, and applied it to make predictions in the other. The predictions were then evaluated by examining the agreements with the known essential genes in the target organism. Ten-fold cross-validation in the same organism yielded AUC scores between 0.86 and 0.93. Cross-organism predictions yielded AUC scores between 0.69 and 0.89. The transferability is likely affected by growth conditions, quality of the training data set and the evolutionary distance. We are thus the first to report that gene essentiality can be reliably predicted using features trained and tested in a distantly related organism. Our approach proves more robust and portable than existing approaches, significantly extending our ability to predict essential genes beyond orthologs.

The characteristics of brain network in patient with post-stroke depression under cognitive task condition.

Objectives: Post-stroke depression (PSD) may be associated with the altered brain network property. This study aimed at exploring the brain network characteristics of PSD under the classic cognitive task, i.e., the oddball task, in order to promote our understanding of the pathogenesis and the diagnosis of PSD. Methods: Nineteen stroke survivors with PSD and 18 stroke survivors with no PSD (non-PSD) were recruited. The functional near-infrared spectroscopy (fNIRS) covering the dorsolateral prefrontal cortex was recorded during the oddball task state and the resting state. The brain network characteristics were extracted using the graph theory and compared between the PSD and the non-PSD subjects. In addition, the classification performance between the PSD and non-PSD subjects was evaluated using features in the resting and the task state, respectively. Results: Compared with the resting state, more brain network characteristics in the task state showed significant differences between the PSD and non-PSD groups, resulting in better classification performance. In the task state, the assortativity, clustering coefficient, characteristic path length, and local efficiency of the PSD subjects was larger compared with the non-PSD subjects while the global efficiency of the PSD subjects was smaller than that of the non-PSD subjects. Conclusion: The altered brain network properties associated with PSD in the cognitive task state were more distinct compared with the resting state, and the ability of the brain network to resist attack and transmit information was reduced in PSD patients in the task state. Significance: This study demonstrated the feasibility and superiority of investigating brain network properties in the task state for the exploration of the pathogenesis and new diagnosis methods for PSD.

Synthesis of End-Cap Enabled Self-Immolative Photoresists For Extreme Ultraviolet Lithography.

Conventional chemically amplified resists (CARs) rely on the usage of photoacid generators to serve as the source of chemical amplification. However, acid diffusion inevitably accompanies CARs and has led to the resolution, line edge roughness, and sensitivity (RLS) trade-off, which is the most challenging technical problem for modern photoresists. Herein, we take advantage of the self-immolative property of polyphthalaldehyde (PPA) derivatives to create end-cap enabled chain scissionable resists for extreme ultraviolet (EUV) lithography. The feasibility of this strategy was demonstrated under UV photodegradation experiments. The dose-to-clear (DTC) under EUV radiation was 90 mJ/cm2 for the most promising resist, representing more than a 100-fold improvement over previous PPA resists. Density functional theory (DFT) calculations were conducted to understand the structural origin of end-cap EUV sensitivity.

QKI 6 ameliorates CIRI through promoting synthesis of triglyceride in neuron and inhibiting neuronal apoptosis associated with SIRT1-PPARγ-PGC-1α axis.

BACKGROUND: The stroke induced by ischemia of brain remains high incidence and death rate. The study wanted to confirm the effects of Quaking 6 (QKI 6) on the protection role in neurons of rat model of cerebral ischemia/reperfusion injury (CIRI). MATERIAL AND METHODS: The rat model with CIRI induced by middle cerebral artery occlusion was well established and rat neurons were isolated to characterize the effects of QKI 6 mediated by sirtuin 1 (SIRT1) on synthesis of triglyceride in neuron and neuronal apoptosis via activation of SIRT1-peroxisome proliferater-activated receptor (PPAR)γ- peroxisome proliferator-activated receptor coactivator (PGC)-1α signaling pathway. RESULTS: The expression levels of SIRT1 or QKI 6, and acetylation level of QKI 6 were decreased in neurons of rat model with CIRI. QKI 6 deacetylated and mediated by SIRT1 that contributed to suppressing the progression of neuronal apoptosis in rat through promoting synthesis of triglyceride in vivo and in vitro via SIRT1-PPARγ-PGC-1α signaling pathway, then inhibiting CIRI. CONCLUSIONS: Our results demonstrated SIRT1 deacetylates QKI 6, the RNA-binding protein, that affects significantly the synthesis of triglyceride in neurons of CIRI rat model. Moreover, it activated transcription factor peroxisome proliferator-activated receptorγ coactivator-1α (PGC-1α) through post-transcriptional regulation of the expression of PPARγ, and further enhanced synthesis of triglyceride, thereby restrained the progression of neural apoptosis and CIRI.

Proteomic characterization of human plasma high density lipoprotein fractionated by gel filtration chromatography.

Plasma levels of high density lipoprotein cholesterol (HDL-C) are inversely proportional to the incidence of cardiovascular disease. Recent applications of modern proteomic technologies have identified upward of 50 distinct proteins associated with HDL particles with many of these newly discovered proteins implicating HDL in nonlipid transport processes including complement activation, acute phase response and innate immunity. However, almost all MS-based proteomic studies on HDL to date have utilized density gradient ultracentrifugation techniques for HDL isolation prior to analysis. These involve high shear forces and salt concentrations that can disrupt HDL protein interactions and alter particle function. Here, we used high-resolution size exclusion chromatography to fractionate normal human plasma to 17 phospholipid-containing subfractions. Then, using a phospholipid binding resin, we identified proteins that associate with lipoproteins of various sizes by electrospray ionization mass spectrometry. We identified 14 new phospholipid-associated proteins that migrate with traditionally defined HDL, several of which further support roles for HDL in complement regulation and protease inhibition. The increased fractionation inherent to this method allowed us to visualize HDL protein distribution across particle size with unprecedented resolution. The observed heterogeneity across subfractions suggests the presence of HDL particle subpopulations each with distinct protein components that may prove to impart distinct physiological functions.

Distance measurements via the morphogen gradient of Bicoid in Drosophila embryos.

BACKGROUND: Patterning along the anterior-posterior (A-P) axis in Drosophila embryos is instructed by the morphogen gradient of Bicoid (Bcd). Despite extensive studies of this morphogen, how embryo geometry may affect gradient formation and target responses has not been investigated experimentally. RESULTS: In this report, we systematically compare the Bcd gradient profiles and its target expression patterns on the dorsal and ventral sides of the embryo. Our results support a hypothesis that proper distance measurement and the encoded positional information of the Bcd gradient are along the perimeter of the embryo. Our results also reveal that the dorsal and ventral sides of the embryo have a fundamentally similar relationship between Bcd and its target Hunchback (Hb), suggesting that Hb expression properties on the two sides of the embryo can be directly traced to Bcd gradient properties. Our 3-D simulation studies show that a curvature difference between the two sides of an embryo is sufficient to generate Bcd gradient properties that are consistent with experimental observations. CONCLUSIONS: The findings described in this report provide a first quantitative, experimental evaluation of embryo geometry on Bcd gradient formation and target responses. They demonstrate that the physical features of an embryo, such as its shape, are integral to how pattern is formed.

Aluminum porphyrins with quaternary ammonium halides as catalysts for copolymerization of cyclohexene oxide and CO2: metal-ligand cooperative catalysis.

Bifunctional AlIII porphyrins with quaternary ammonium halides, 2-Cl and 2-Br, worked as excellent catalysts for the copolymerization of cyclohexene oxide (CHO) and CO2 at 120 °C. Turnover frequency (TOF) and turnover number (TON) reached 10 000 h-1 and 55 000, respectively, and poly(cyclohexene carbonate) (PCHC) with molecular weight of up to 281 000 was obtained with a catalyst loading of 0.001 mol%. In contrast, bifunctional MgII and ZnII counterparts, 3-Cl and 4-Cl, as well as a binary catalyst system, 1-Cl with bis(triphenylphosphine)iminium chloride (PPNCl), showed poor catalytic performances. Kinetic studies revealed that the reaction rate was first-order in [CHO] and [2-Br] and zero-order in [CO2], and the activation parameters were determined: ΔH ‡ = 12.4 kcal mol-1, ΔS ‡ = -26.1 cal mol-1 K-1, and ΔG ‡ = 21.6 kcal mol-1 at 80 °C. Comparative DFT calculations on two model catalysts, AlIII complex 2' and MgII complex 3', allowed us to extract key factors in the catalytic behavior of the bifunctional AlIII catalyst. The high polymerization activity and carbonate-linkage selectivity originate from the cooperative actions of the metal center and the quaternary ammonium cation, both of which facilitate the epoxide-ring opening by the carbonate anion to form the carbonate linkage in the key transition state such as TS3b (ΔH ‡ = 13.3 kcal mol-1, ΔS ‡ = -3.1 cal mol-1 K-1, and ΔG ‡ = 14.4 kcal mol-1 at 80 °C).

Expert consensus on protocol of rehabilitation for COVID-19 patients using framework and approaches of WHO International Family Classifications.

Coronavirus disease 2019 (COVID-19) has widely spread all over the world and the numbers of patients and deaths are increasing. According to the epidemiology, virology, and clinical practice, there are varying degrees of changes in patients, involving the human body structure and function and the activity and participation. Based on the World Health Organization (WHO) International Classification of Functioning, Disability and Health (ICF) and its biopsychosocial model of functioning, we use the WHO Family of International Classifications (WHO-FICs) framework to form an expert consensus on the COVID-19 rehabilitation program, focusing on the diagnosis and evaluation of disease and functioning, and service delivery of rehabilitation, and to establish a standard rehabilitation framework, terminology system, and evaluation and intervention systems based the WHO-FICs.

In utero gene expression in the Slc39a8(neo/neo) knockdown mouse.

Slc39a8 encodes ZIP8, a divalent cation/bicarbonate symporter expressed in pluripotent mouse embryonic stem cells, and therefore ubiquitous in adult tissues; ZIP8 influxes Zn2+, Mn2+ and Fe2+. Slc39a8(neo/neo) knockdown mice exhibit 10-15% of wild-type ZIP8 mRNA and protein levels, and show pleiotropic phenotype of stunted growth, neonatal lethality, multi-organ dysmorphogenesis, and dysregulated hematopoiesis manifested as severe anemia. Herein we performed RNA-seq analysis of gestational day (GD)13.5 yolk sac and placenta, and GD16.5 liver, kidney, lung, heart and cerebellum, comparing Slc39a8(neo/neo) with Slc39a8(+/+) wild-type. Meta-data analysis of differentially-expressed genes revealed 29 unique genes from all tissues - having enriched GO categories associated with hematopoiesis and hypoxia and KEGG categories of complement, response to infection, and coagulation cascade - consistent with dysregulated hematopoietic stem cell fate. Based on transcription factor (TF) profiles in the JASPAR database, and searching for TF-binding sites enriched by Pscan, we identified numerous genes encoding zinc-finger and other TFs associated with hematopoietic stem cell functions. We conclude that, in this mouse model, deficient ZIP8-mediated divalent cation transport affects zinc-finger (e.g. GATA proteins) and other TFs interacting with GATA proteins (e.g. TAL1), predominantly in yolk sac. These data strongly support the phenotype of dysmorphogenesis and anemia seen in Slc39a8(neo/neo) mice in utero.

An integrated machine-learning model to predict prokaryotic essential genes.

Essential genes are indispensable for the target organism's survival. Large-scale identification and characterization of essential genes has shown to be beneficial in both fundamental biology and medicine fields. Current existing genome-scale experimental screenings of essential genes are time consuming and costly, also sometimes confer erroneous essential gene annotations. To circumvent these difficulties, many research groups turn to computational approaches as the alternative to identify essential genes. Here, we developed an integrative machine-learning based statistical framework to accurately predict essential genes in microorganisms. First we extracted a variety of relevant features derived from different aspects of an organism's genomic sequences. Then we selected a subset of features have high predictive power of gene essentiality through a carefully designed feature selection system. Using the selected features as input, we constructed an ensemble classifier and trained the model on a well-studied microorganism. After fine-tuning the model parameters in cross-validation, we tested the model on the other microorganism. We found that the tenfold cross-validation results within the same organism achieves a high predictive accuracy (AUC ~0.9), and cross-organism predictions between distant related organisms yield the AUC scores from 0.69 to 0.89, which significantly outperformed homology mapping.

A statistical framework for improving genomic annotations of transposon mutagenesis (TM) assigned essential genes.

Whole-genome transposon mutagenesis (TM) experiment followed by sequence-based identification of insertion sites is the most popular genome-wise experiment to identify essential genes in Prokaryota. However, due to the limitation of high-throughput technique, this approach yields substantial systematic biases resulting in the incorrect assignments of many essential genes. To obtain unbiased and accurate annotations of essential genes from TM experiments, we developed a novel Poisson model based statistical framework to refine these TM assignments. In the model, first we identified and incorporated several potential factors such as gene length and TM insertion information which may cause the TM assignment biases into the basic Poisson model. Then we calculated the conditional probability of an essential gene given the observed TM insertion number. By factorizing this probability through introducing a latent variable the real insertion number, we formalized the statistical framework. Through iteratively updating and optimizing model parameters to maximize the goodness-of-fit of the model to the observed TM insertion data, we finalized the model. Using this model, we are able to assign the probability score of essentiality to each individual gene given its TM assignment, which subsequently correct the experimental biases. To enable our model widely useable, we established a user-friendly Web-server that is accessible to the public: http://research.cchmc.org/essentialgene/.