We demonstrated the use of the KEGG Orthology (KO), part of the KEGG suite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available stand-alone Python program that can contribute significantly to genome annotation and microarray analysis.

There is an increasing need to automatically annotate a set of genes or proteins (from genome sequencing, DNA microarray analysis or protein 2D gel experiments) using controlled vocabularies and identify the pathways involved, especially the statistically enriched pathways. We have previously demonstrated the KEGG Orthology (KO) as an effective alternative controlled vocabulary and developed a standalone KO-Based Annotation System (KOBAS). Here we report a KOBAS server with a friendly web-based user interface and enhanced functionalities. The server can support input by nucleotide or amino acid sequences or by sequence identifiers in popular databases and can annotate the input with KO terms and KEGG pathways by BLAST sequence similarity or directly ID mapping to genes with known annotations. The server can then identify both frequent and statistically enriched pathways, offering the choices of four statistical tests and the option of multiple testing correction. The server also has a ‘User Space’ in which frequent users may store and manage their data and results online. We demonstrate the usability of the server by finding statistically enriched pathways in a set of upregulated genes in Alzheimer's Disease (AD) hippocampal cornu ammonis 1 (CA1). KOBAS server can be accessed at .

The mitochondrial pathway of apoptosis is controlled by the ratio of anti-and pro-apoptotic members of the Bcl-2 family of proteins. The molecular events underlying how a given physiological stimulus changes this ratio to trigger apoptosis remains unclear. We report here that human 17-b-estradiol (E2) and its related steroid hormones induce apoptosis by binding directly to phosphodiesterase 3A, which in turn recruits and stabilizes an otherwise fast-turnover protein Schlafen 12 (SLFN12). The elevated SLFN12 binds to ribosomes to exclude the recruitment of signal recognition particles (SRPs), thereby blocking the continuous protein translation occurring on the endoplasmic reticulum of E2-treated cells. These proteins include Bcl-2 and Mcl-1, whose ensuing decrease triggers apoptosis. The SLFN12 protein and an apoptosis activation marker were co-localized in syncytiotrophoblast of human placentas, where levels of estrogen-related hormones are high, and dynamic cell turnover by apoptosis is critical for successful implantation and placenta development.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume < 15 μL at concentrations < 5pg/mL while only requiring a 5-min assay incubation, allowing for all processes from sampling to result to be completed within 40 min. The assay procedure applies both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduces errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 12 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy reveals the powerful biomarker profiling capability. The assay could also be deployed for near-real-time immune status monitoring of critically ill COVID-19 patients developing cytokine storm syndrome.

Reduction of mitochondrial membrane potential (Δψm) is a hallmark of mitochondrial dysfunction. It activates adaptive responses in organisms from yeast to human to rewire metabolism, remove depolarized mitochondria, and degrade unimported precursor proteins. It remains unclear how cells maintain Δψm, which is critical for maintaining iron‐sulfur cluster (ISC) synthesis, an indispensable function of mitochondria. Here, we show that yeast oxidative phosphorylation mutants deficient in complex III, IV, V, and mtDNA, respectively, exhibit activated stress responses and progressive reduction of Δψm. Extensive omics analyses of these mutants show that these mutants progressively activate adaptive responses, including transcriptional downregulation of ATP synthase inhibitor Inh1 and OXPHOS subunits, Puf3‐mediated upregulation of import receptor Mia40 and global mitochondrial biogenesis, Snf1/AMPK‐mediated upregulation of glycolysis and repression of ribosome biogenesis, and transcriptional upregulation of cytoplasmic chaperones. These adaptations disinhibit mitochondrial ATP hydrolysis, remodel mitochondrial proteome, and optimize ATP supply to mitochondria to convergently maintain Δψm, ISC biosynthesis, and cell proliferation.

A digital microfluidic immunoassay platform enables rapid multiplex quantification of proinflammatory cytokines in serum for critically ill COVID-19 patients.

Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. However, translating digital protein assays to acute clinical care has been challenging because it requires their deployment with a rapid turnaround. Herein, we present a technology platform for ultra-fast digital protein biomarker detection by employing single-molecule counting of immune-complex formation events at an early, pre-equilibrium state. This method, which we term "pre-equilibrium digital enzyme-linked immunosorbent assay" (PEdELISA), can quantify a multiplexed panel of protein biomarkers in 10 µL of serum within an unprecedented assay incubation time of 15-300 sec over a 104 dynamic range. PEdELISA allowed us to perform rapid monitoring of protein biomarkers in patients manifesting post-chimeric antigen receptor T-cell (CAR-T) therapy cytokine release syndrome (CRS), with ~30 min sample-to-answer time and a sub-pg/mL limit of detection (LOD). The rapid, sensitive, and low input volume biomarker quantification enabled by PEdELISA is broadly applicable to timely monitoring of acute disease, potentially enabling more personalized treatment.

Background:Romidepsin (FK228) or depsipeptide, is a selective inhibitor of histone deacetylase 1 (HDAC1) and HDAC2. This study aimed to investigate the effects and molecular mechanisms of romidepsin (FK228) in a mouse model of acute kidney injury (AKI) induced by lipopolysaccharide (LPS). Material/Methods:The mouse model of AKI was developed by intraperitoneal injection of LPS. The mice were also treated intraperitoneally with romidepsin (FK228) six hours following injection of LPS. Markers of renal injury were measured, including blood urea nitrogen (BUN), serum creatinine (SCR), and serum cystatin C (Cys C) were measured. Histology and transmission electron microscopy were performed to evaluate tissue injury further. Levels of HDACs were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. Coimmunoprecipitation (Co-IP) and chromatin immunoprecipitation (ChIP) assays were used to investigate the regulation of CYP2E1 expression. Results:Treatment with romidepsin (FK228) significantly reduced the levels of BUN, SCR, and Cys C induced by LPS. Histology of the mouse kidneys showed that treatment with romidepsin (FK228) reduced the degree of renal injury. CYP2E1 significantly reduced following treatment with romidepsin (FK228) in the mouse model of AKI. Also, acetylation of H3 was upregulated following treatment with romidepsin (FK228), and binding of hepatocyte nuclear factor-1 alpha (HNF-1a) on the CYP2E1 promoter was significantly increased. Conclusions:In a mouse model of LPS-induced AKI, treatment with romidepsin (FK228) downregulated the expression of CYP2E1 by inhibiting the binding if HNF-1a with the CYP2E1 promoter to reduce renal injury.