IFNγ-Dependent Tissue-Immune Homeostasis Is Co-opted in the Tumor Microenvironment.

Homeostatic programs balance immune protection and self-tolerance. Such mechanisms likely impact autoimmunity and tumor formation, respectively. How homeostasis is maintained and impacts tumor surveillance is unknown. Here, we find that different immune mononuclear phagocytes share a conserved steady-state program during differentiation and entry into healthy tissue. IFNγ is necessary and sufficient to induce this program, revealing a key instructive role. Remarkably, homeostatic and IFNγ-dependent programs enrich across primary human tumors, including melanoma, and stratify survival. Single-cell RNA sequencing (RNA-seq) reveals enrichment of homeostatic modules in monocytes and DCs from human metastatic melanoma. Suppressor-of-cytokine-2 (SOCS2) protein, a conserved program transcript, is expressed by mononuclear phagocytes infiltrating primary melanoma and is induced by IFNγ. SOCS2 limits adaptive anti-tumoral immunity and DC-based priming of T cells in vivo, indicating a critical regulatory role. These findings link immune homeostasis to key determinants of anti-tumoral immunity and escape, revealing co-opting of tissue-specific immune development in the tumor microenvironment.

Alternative polyadenylation determines the functional landscape of inverted Alu repeats.

Inverted Alu repeats (IRAlus) are abundantly found in the transcriptome, especially in introns and 3' untranslated regions (UTRs). Yet, the biological significance of IRAlus embedded in 3' UTRs remains largely unknown. Here, we find that 3' UTR IRAlus silences genes involved in essential signaling pathways. We utilize J2 antibody to directly capture and map the double-stranded RNA structure of 3' UTR IRAlus in the transcriptome. Bioinformatic analysis reveals alternative polyadenylation as a major axis of IRAlus-mediated gene regulation. Notably, the expression of mouse double minute 2 (MDM2), an inhibitor of p53, is upregulated by the exclusion of IRAlus during UTR shortening, which is exploited to silence p53 during tumorigenesis. Moreover, the transcriptome-wide UTR lengthening in neural progenitor cells results in the global downregulation of genes associated with neurodegenerative diseases, including amyotrophic lateral sclerosis, via IRAlus inclusion. Our study establishes the functional landscape of 3' UTR IRAlus and its role in human pathophysiology.

The SARS-CoV-2 RNA interactome.

SARS-CoV-2 is an RNA virus whose success as a pathogen relies on its abilities to repurpose host RNA-binding proteins (RBPs) and to evade antiviral RBPs. To uncover the SARS-CoV-2 RNA interactome, we here develop a robust ribonucleoprotein (RNP) capture protocol and identify 109 host factors that directly bind to SARS-CoV-2 RNAs. Applying RNP capture on another coronavirus, HCoV-OC43, revealed evolutionarily conserved interactions between coronaviral RNAs and host proteins. Transcriptome analyses and knockdown experiments delineated 17 antiviral RBPs, including ZC3HAV1, TRIM25, PARP12, and SHFL, and 8 proviral RBPs, such as EIF3D and CSDE1, which are responsible for co-opting multiple steps of the mRNA life cycle. This also led to the identification of LARP1, a downstream target of the mTOR signaling pathway, as an antiviral host factor that interacts with the SARS-CoV-2 RNAs. Overall, this study provides a comprehensive list of RBPs regulating coronaviral replication and opens new avenues for therapeutic interventions.

Molecular Basis for the Single-Nucleotide Precision of Primary microRNA Processing.

Microprocessor, composed of DROSHA and its cofactor DGCR8, initiates microRNA (miRNA) biogenesis by processing the primary transcripts of miRNA (pri-miRNAs). Here we investigate the mechanism by which Microprocessor selects the cleavage site with single-nucleotide precision, which is crucial for the specificity and functionality of miRNAs. By testing ∼40,000 pri-miRNA variants, we find that for some pri-miRNAs the cleavage site is dictated mainly by the mGHG motif embedded in the lower stem region of pri-miRNA. Structural modeling and deep-sequencing-based complementation experiments show that the double-stranded RNA-binding domain (dsRBD) of DROSHA recognizes mGHG to place the catalytic center in the appropriate position. The mGHG motif as well as the mGHG-recognizing residues in DROSHA dsRBD are conserved across eumetazoans, suggesting that this mechanism emerged in an early ancestor of the animal lineage. Our findings provide a basis for the understanding of miRNA biogenesis and rational design of accurate small-RNA-based gene silencing.

Noncanonical immune response to the inhibition of DNA methylation by Staufen1 via stabilization of endogenous retrovirus RNAs.

DNA-methyltransferase inhibitors (DNMTis), such as azacitidine and decitabine, are used clinically to treat myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Decitabine activates the transcription of endogenous retroviruses (ERVs), which can induce immune response by acting as cellular double-stranded RNAs (dsRNAs). Yet, the posttranscriptional regulation of ERV dsRNAs remains uninvestigated. Here, we find that the viral mimicry and subsequent cell death in response to decitabine require the dsRNA-binding protein Staufen1 (Stau1). We show that Stau1 directly binds to ERV RNAs and stabilizes them in a genome-wide manner. Furthermore, Stau1-mediated stabilization requires a long noncoding RNA TINCR, which enhances the interaction between Stau1 and ERV RNAs. Analysis of a clinical patient cohort reveals that MDS and AML patients with lower Stau1 and TINCR expressions exhibit inferior treatment outcomes to DNMTi therapy. Overall, our study reveals the posttranscriptional regulatory mechanism of ERVs and identifies the Stau1-TINCR complex as a potential target for predicting the efficacy of DNMTis and other drugs that rely on dsRNAs.

Introducing MdTFL1 Promotes Heading Date and Produces Semi-Draft Phenotype in Rice.

Flowering time (in rice, termed the heading date), plant height, and grain number are crucial agronomic traits for rice productivity. The heading date is controlled via environmental factors (day length and temperature) and genetic factors (floral genes). TERMINAL FLOWER 1 (TFL1) encodes a protein that controls meristem identity and participates in regulating flowering. In this study, a transgenic approach was used to promote the heading date in rice. We isolated and cloned apple MdTFL1 for early flowering in rice. Transgenic rice plants with antisense MdTFL1 showed an early heading date compared with wild-type plants. A gene expression analysis suggested that introducing MdTFL1 upregulated multiple endogenous floral meristem identity genes, including the (early) heading date gene family FLOWERING LOCUS T and MADS-box transcription factors, thereby shortening vegetable development. Antisense MdTFL1 also produced a wide range of phenotypic changes, including a change in overall plant organelles that affected an array of traits, especially grain productivity. The transgenic rice exhibited a semi-draft phenotype, increased leaf inclination angle, restricted flag leaf length, reduced spikelet fertility, and fewer grains per panicle. MdTFL1 plays a central role in regulating flowering and in various physiological aspects. These findings emphasize the role of TFL1 in regulating flowering in shortened breeding and expanding its function to produce plants with semi-draft phenotypes.

The Synergistic Effects of Environmental and Genetic Factors on the Regulation of Anthocyanin Accumulation in Plant Tissues.

Anthocyanin accumulation is responsible for the coloration of apple fruit, and their accumulation depends on the expression of anthocyanin biosynthesis-related genes. Light is an environmental stimulus that induces fruit color by regulating genes involved in the anthocyanin biosynthesis pathway. In this study, the roles of light and genetic factors on fruit coloration and anthocyanin accumulation in apple fruit were investigated. Three genes in the anthocyanin biosynthesis pathway, MdCHS, MdANS, and MdUFGT1, were synthesized and cloned into a viral-based expression vector system for transient expression in 'Ruby S' apple fruits. Apple fruits were agroinfiltrated with expression vectors harboring MdCHS, MdANS, and MdUFGT1. Agroinfiltrated apple fruits were then either kept in the dark (bagged fruits) or exposed to light (exposed fruits). The agroinfiltrated fruits showed significantly different coloration patterns, transcript expression levels, and anthocyanin accumulation compared to the control fruits. Moreover, these parameters were higher in exposed fruits than in bagged fruits. For stable expression, MdCHS was introduced into a binary vector under the control of the rice α-amylase 3D (RAmy3D) promoter. The ectopic overexpression of MdCHS in transgenic rice calli showed a high accumulation of anthocyanin content. Taken together, our findings suggest that light, together with the overexpression of anthocyanin biosynthesis genes, induced the coloration and accumulation of anthocyanin content in apple fruits by upregulating the expression of the genes involved in the anthocyanin biosynthesis pathway.

Antisense Expression of Apple TFL1-like Gene (MdTFL1) Promotes Early Flowering and Causes Phenotypic Changes in Tobacco.

Apples (Malus × domestica Borkh.) require up to several years for flowering and bearing fruits. The transition from vegetative to reproductive phase is controlled by floral regulators such as TERMINAL FLOWER 1 (TFL1) and FLOWERING LOCUS T (FT). TFL1 mediates the maintenance of vegetative phase, unlike the antagonistic function of FT to promote the transition into reproductive phase. In this study, we isolated apple TFL1-like gene (MdTFL1) to elucidate various phenotypic traits triggered by the antisense expression of MdTFL1 in tobacco apart from its floral induction function. Early flowering was observed in the tobacco line with MdTFL1 knockout, indicating the reduced time for transition to vegetative phases. Quantitative reverse-transcription PCR showed upregulation of genes involved in the regulation of floral induction, including NtAP1, NtSOC1, NFL1, and NtFTs, and downregulation of carotenoid cleavage dioxygenases (CCDs) and CEN-like genes in transgenic lines. Interestingly, transgenic tobacco expressing antisense MdTFL1 exhibited distinct morphological changes in lateral shoot outgrowth, internode length, and the development of leaves, flowers, and fruits. The results suggested that using the antisense expression of MdTFL1 gene is one of the approaches to shorten the vegetable phase and proposed improvement of plant architecture in horticultural crops.

Light Induces Carotenoid Biosynthesis-Related Gene Expression, Accumulation of Pigment Content, and Expression of the Small Heat Shock Protein in Apple Fruit.

The coloration of the apple fruit (Malus × domestica Borkh.) depends on pigment content. Light stimulus activates a broad range of photosynthesis-related genes, including carotenoids. The effect of light on two red commercial apple cultivars, 'Summer Prince' and 'Arisoo' at the juvenile stage were examined. Apple fruits were either bagged to reduce light irradiation or were exposed to direct, enhanced sunlight (reflected). The pigment content and the expression of carotenoid metabolism genes in the peel and flesh of apple fruits were significantly different between the shaded and the reflected parts. These parameters were also different in the two cultivars, highlighting the contribution of the genetic background. Further, a combination of light and transient overexpression of carotenogenic genes increased fruit coloration and pigment content in the variety 'RubyS'. Western blot analysis showed the expression of small heat shock proteins (smHSP) in lysates extracted from the reflected part of the fruits but not in the bagged fruits, indicating the activation of smHSP in response to heat generated by the reflected light. Therefore, the synergy between the genes and the environment dictates the color of apple fruits.

Interpretation of an individual functional genomics experiment guided by massive public data.

A key unmet challenge in interpreting omics experiments is inferring biological meaning in the context of public functional genomics data. We developed a computational framework, Your Evidence Tailored Integration (YETI; http://yeti.princeton.edu/ ), which creates specialized functional interaction maps from large public datasets relevant to an individual omics experiment. Using this tailored integration, we predicted and experimentally confirmed an unexpected divergence in viral replication after seasonal or pandemic human influenza virus infection.

MS1-Level Proteome Quantification Platform Allowing Maximally Increased Multiplexity for SILAC and In Vitro Chemical Labeling.

Quantitative proteomic platforms based on precursor intensity in mass spectrometry (MS1-level) uniquely support in vivo metabolic labeling with superior quantification accuracy but suffer from limited multiplexity (≤3-plex) and frequent missing quantities. Here we present a new MS1-level quantification platform that allows maximal multiplexing with high quantification accuracy and precision for the given labeling scheme. The platform currently comprises 6-plex in vivo SILAC or in vitro diethylation labeling with a dedicated algorithm and is also expandable to higher multiplexity (e.g., nine-plex for SILAC). For complex samples with broad dynamic ranges such as total cell lysates, our platform performs highly accurately and free of missing quantities. Furthermore, we successfully applied our method to measure protein synthesis rate under heat shock response in human cells by 6-plex pulsed SILAC experiments, demonstrating the unique biological merits of our in vivo platform to disclose translational regulations for cellular response to stress.

Defining cell-type specificity at the transcriptional level in human disease.

Cell-lineage-specific transcripts are essential for differentiated tissue function, implicated in hereditary organ failure, and mediate acquired chronic diseases. However, experimental identification of cell-lineage-specific genes in a genome-scale manner is infeasible for most solid human tissues. We developed the first genome-scale method to identify genes with cell-lineage-specific expression, even in lineages not separable by experimental microdissection. Our machine-learning-based approach leverages high-throughput data from tissue homogenates in a novel iterative statistical framework. We applied this method to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary and most acquired glomerular kidney disease. In a systematic evaluation of our predictions by immunohistochemistry, our in silico approach was significantly more accurate (65% accuracy in human) than predictions based on direct measurement of in vivo fluorescence-tagged murine podocytes (23%). Our method identified genes implicated as causal in hereditary glomerular disease and involved in molecular pathways of acquired and chronic renal diseases. Furthermore, based on expression analysis of human kidney disease biopsies, we demonstrated that expression of the podocyte genes identified by our approach is significantly related to the degree of renal impairment in patients. Our approach is broadly applicable to define lineage specificity in both cell physiology and human disease contexts. We provide a user-friendly website that enables researchers to apply this method to any cell-lineage or tissue of interest. Identified cell-lineage-specific transcripts are expected to play essential tissue-specific roles in organogenesis and disease and can provide starting points for the development of organ-specific diagnostics and therapies.

Tissue-aware data integration approach for the inference of pathway interactions in metazoan organisms.

MOTIVATION: Leveraging the large compendium of genomic data to predict biomedical pathways and specific mechanisms of protein interactions genome-wide in metazoan organisms has been challenging. In contrast to unicellular organisms, biological and technical variation originating from diverse tissues and cell-lineages is often the largest source of variation in metazoan data compendia. Therefore, a new computational strategy accounting for the tissue heterogeneity in the functional genomic data is needed to accurately translate the vast amount of human genomic data into specific interaction-level hypotheses. RESULTS: We developed an integrated, scalable strategy for inferring multiple human gene interaction types that takes advantage of data from diverse tissue and cell-lineage origins. Our approach specifically predicts both the presence of a functional association and also the most likely interaction type among human genes or its protein products on a whole-genome scale. We demonstrate that directly incorporating tissue contextual information improves the accuracy of our predictions, and further, that such genome-wide results can be used to significantly refine regulatory interactions from primary experimental datasets (e.g. ChIP-Seq, mass spectrometry). AVAILABILITY AND IMPLEMENTATION: An interactive website hosting all of our interaction predictions is publically available at http://pathwaynet.princeton.edu. Software was implemented using the open-source Sleipnir library, which is available for download at https://bitbucket.org/libsleipnir/libsleipnir.bitbucket.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PHO13 deletion-induced transcriptional activation prevents sedoheptulose accumulation during xylose metabolism in engineered Saccharomyces cerevisiae.

The deletion of PHO13 (pho13Δ) in Saccharomyces cerevisiae, encoding a phosphatase enzyme of unknown specificity, results in the transcriptional activation of genes related to the pentose phosphate pathway (PPP) such as TAL1 encoding transaldolase. It has been also reported that the pho13Δ mutant of S. cerevisiae expressing a heterologous xylose pathway can metabolize xylose efficiently compared to its parental strain. However, the interaction between the pho13Δ-induced transcriptional changes and the phenotypes of xylose fermentation was not understood. Thus we investigated the global metabolic changes in response to pho13Δ when cells were exponentially growing on xylose. Among the 134 intracellular metabolites that we identified, the 98% reduction of sedoheptulose was found to be the most significant change in the pho13Δ mutant as compared to its parental strain. Because sedoheptulose-7-phosphate (S7P), a substrate of transaldolase, reduced significantly in the pho13Δ mutant as well, we hypothesized that limited transaldolase activity in the parental strain might cause dephosphorylation of S7P, leading to carbon loss and inefficient xylose metabolism. Mutants overexpressing TAL1 at different degrees were constructed, and their TAL1 expression levels and xylose consumption rates were positively correlated. Moreover, as TAL1 expression levels increased, intracellular sedoheptulose concentration dropped significantly. Therefore, we concluded that TAL1 upregulation, preventing the accumulation of sedoheptulose, is the most critical mechanism for the improved xylose metabolism by the pho13Δ mutant of engineered S. cerevisiae.

Ontology-aware classification of tissue and cell-type signals in gene expression profiles across platforms and technologies.

MOTIVATION: Leveraging gene expression data through large-scale integrative analyses for multicellular organisms is challenging because most samples are not fully annotated to their tissue/cell-type of origin. A computational method to classify samples using their entire gene expression profiles is needed. Such a method must be applicable across thousands of independent studies, hundreds of gene expression technologies and hundreds of diverse human tissues and cell-types. RESULTS: We present Unveiling RNA Sample Annotation (URSA) that leverages the complex tissue/cell-type relationships and simultaneously estimates the probabilities associated with hundreds of tissues/cell-types for any given gene expression profile. URSA provides accurate and intuitive probability values for expression profiles across independent studies and outperforms other methods, irrespective of data preprocessing techniques. Moreover, without re-training, URSA can be used to classify samples from diverse microarray platforms and even from next-generation sequencing technology. Finally, we provide a molecular interpretation for the tissue and cell-type models as the biological basis for URSA's classifications.

Deadenylation kinetics of mixed poly(A) tails at single-nucleotide resolution.

Shortening of messenger RNA poly(A) tails, or deadenylation, is a rate-limiting step in mRNA decay and is highly regulated during gene expression. The incorporation of non-adenosines in poly(A) tails, or 'mixed tailing', has been observed in vertebrates and viruses. Here, to quantitate the effect of mixed tails, we mathematically modeled deadenylation reactions at single-nucleotide resolution using an in vitro deadenylation system reconstituted with the complete human CCR4-NOT complex. Applying this model, we assessed the disrupting impact of single guanosine, uridine or cytosine to be equivalent to approximately 6, 8 or 11 adenosines, respectively. CCR4-NOT stalls at the 0, -1 and -2 positions relative to the non-adenosine residue. CAF1 and CCR4 enzyme subunits commonly prefer adenosine but exhibit distinct sequence selectivities and stalling positions. Our study provides an analytical framework to monitor deadenylation and reveals the molecular basis of tail sequence-dependent regulation of mRNA stability.

Pelvic floor muscle training using an extracorporeal biofeedback device for female stress urinary incontinence.

INTRODUCTION AND HYPOTHESIS: Extracorporeal biofeedback was developed to reduce patient discomfort when performing strengthening exercises. The efficacy and safety of extracorporeal biofeedback combined with pelvic floor muscle training (PFMT) for the treatment of female stress urinary incontinence (SUI) were evaluated. METHODS: One hundred and six participants with SUI were enrolled in a 12-week PFMT program using extracorporeal biofeedback intervention. A standard pad test was performed, and pelvic floor muscle strength was assessed using the Oxford scale. Measurements were taken with a perineometer at baseline and at a 12-week follow-up visit. An objective cure was defined as less than 2 g of urine leakage by the standard pad test. The long-term effects of extracorporeal biofeedback and PFMT were investigated by interviewing the participants 12 months after treatment. RESULTS: Seventy-one participants completed the 12-week extracorporeal biofeedback intervention. The objective cure rate was 52.1 %, and there was a significant reduction in pad weight over the time period. The incontinence visual analogue scale, the Sandvik severity index, and the incontinence quality-of-life questionnaire domains were significantly improved after treatment (p<0.001). The strength of the PFM was significantly increased after the 12-week treatment. After PFMT, 64.3 % of 56 participants reported good treatment compliance, and 24 participants (42.9 %) had continued PFMT at home 12 months after treatment. Age and baseline pad weight were negative predictive factors for an objective cure of SUI. CONCLUSIONS: Pelvic floor muscle training using extracorporeal biofeedback can be an effective and safe conservative treatment option for female SUI without the discomfort caused by vaginal sensors.

Diagnostic role of prostate resection in the elderly patients who experience significant co-morbidity with a high clinical suspicion of prostate cancer.

The necessity of routine prostate biopsy prior to transurethral resection of the prostate (TURP) in elderly comorbid patients with a high prostate specific antigen (PSA) level remains controversial. We assessed the role of TURP in prostate cancer diagnosis in these individuals. A total of 197 patients underwent TURP in conjunction with prostatic needle biopsy. Pathologic reviews of specimens of TUR chips and biopsy cores were analyzed. Overall, prostate cancer (CaP) was detected in 114 patients (57.6%). Ninety-eight cancers (86%) were detected with TURP and biopsy, and seven cancers (6.1%) with only TURP. The Gleason score of a TUR-specimen was identical to that of the biopsy-core in 43.9% of cases. Variables associated with diagnostic accuracy in the TUR-specimens included the prebiopsy PSA level, prostate specific antigen density (PSAD), and the Gleason score in biopsy cores. In patients with a PSA level and a PSAD that was greater than 15.4 ng/mL and 0.69 ng/mL/g, respectively, 100% of the cancers were detected in the TUR-specimens. Our results suggest that a prostatic biopsy might be omitted prior to TURP in elderly patients with significant co-morbidity and levels for PSA of >15.4 ng/mL.

Short poly(A) tails are protected from deadenylation by the LARP1-PABP complex.

Deadenylation generally constitutes the first and pivotal step in eukaryotic messenger RNA decay. Despite its importance in posttranscriptional regulations, the kinetics of deadenylation and its regulation remain largely unexplored. Here we identify La ribonucleoprotein 1, translational regulator (LARP1) as a general decelerator of deadenylation, which acts mainly in the 30-60-nucleotide (nt) poly(A) length window. We measured the steady-state and pulse-chased distribution of poly(A)-tail length, and found that deadenylation slows down in the 30-60-nt range. LARP1 associates preferentially with short tails and its depletion results in accelerated deadenylation specifically in the 30-60-nt range. Consistently, LARP1 knockdown leads to a global reduction of messenger RNA abundance. LARP1 interferes with the CCR4-NOT-mediated deadenylation in vitro by forming a ternary complex with poly(A)-binding protein (PABP) and poly(A). Together, our work reveals a dynamic nature of deadenylation kinetics and a role of LARP1 as a poly(A) length-specific barricade that creates a threshold for deadenylation.

Prediction of anti-vascular endothelial growth factor agent-specific treatment outcomes in neovascular age-related macular degeneration using a generative adversarial network.

To develop an artificial intelligence (AI) model that predicts anti-vascular endothelial growth factor (VEGF) agent-specific anatomical treatment outcomes in neovascular age-related macular degeneration (AMD), thereby assisting clinicians in selecting the most suitable anti-VEGF agent for each patient. This retrospective study included patients diagnosed with neovascular AMD who received three loading injections of either ranibizumab or aflibercept. Training was performed using optical coherence tomography (OCT) images with an attention generative adversarial network (GAN) model. To test the performance of the AI model, the sensitivity and specificity to predict the presence of retinal fluid after treatment were calculated for the AI model, an experienced (Examiner 1), and a less experienced (Examiner 2) human examiners. A total of 1684 OCT images from 842 patients (419 treated with ranibizumab and 423 treated with aflibercept) were used as the training set. Testing was performed using images from 98 patients. In patients treated with ranibizumab, the sensitivity and specificity, respectively, were 0.615 and 0.667 for the AI model, 0.385 and 0.861 for Examiner 1, and 0.231 and 0.806 for Examiner 2. In patients treated with aflibercept, the sensitivity and specificity, respectively, were 0.857 and 0.881 for the AI model, 0.429 and 0.976 for Examiner 1, and 0.429 and 0.857 for Examiner 2. In 18.5% of cases, the fluid status of synthetic posttreatment images differed between ranibizumab and aflibercept. The AI model using GAN might predict anti-VEGF agent-specific short-term treatment outcomes with relatively higher sensitivity than human examiners. Additionally, there was a difference in the efficacy in fluid resolution between the anti-VEGF agents. These results suggest the potential of AI in personalized medicine for patients with neovascular AMD.