Abstract The response of ectotherms to temperature stress is complex, non-linear, and is influenced by life stage and previous thermal exposure. Mortality is higher under constant low temperatures than under a fluctuating thermal regime (FTR) that maintains the same low temperature but adds a brief, daily pulse of increased temperature. Long term exposure to FTR has been shown to increase transcription of genes involved in oxidative stress, immune function, and metabolic pathways, which may aid in recovery from chill injury and oxidative damage. Previous research suggests the transcriptional response that protects against sub-lethal damage occurs rapidly under exposure to fluctuating temperatures. However, existing studies have only examined gene expression after a week or over many months. Here we characterize gene expression during a single temperature cycle under FTR. Development of pupating alfalfa leafcutting bees (Megachile rotundata) was interrupted at the red-eye stage and were transferred to 6°C with a 1-h pulse to 20°C and returned to 6°C. RNA was collected before, during, and after the temperature pulse and compared to pupae maintained at a static 6°C. The warm pulse is sufficient to cause expression of transcripts that repair cell membrane damage, modify membrane composition, produce antifreeze proteins, restore ion homeostasis, and respond to oxidative stress. This pattern of expression indicates that even brief exposure to warm temperatures has significant protective effects on insects exposed to stressful cold temperatures that persist beyond the warm pulse. Megachile rotundata’s sensitivity to temperature fluctuations indicates that short exposures to temperature changes affect development and physiology. Genes associated with developmental patterning are expressed after the warm pulse, suggesting that 1 h at 20°C was enough to resume development in the pupae. The greatest difference in gene expression occurred between pupae collected after the warm pulse and at constant low temperatures. Although both were collected at the same time and temperature, the transcriptional response to one FTR cycle included multiple transcripts previously identified under long-term FTR exposure associated with recovery from chill injury, indicating that the effects of FTR occur rapidly and are persistent.
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A recursive framework for predicting the time-course of drug sensitivity
The biological processes involved in a drug’s mechanisms of action are oftentimes dynamic, complex and difficult to discern. Time-course gene expression data is a rich source of information that can be used to unravel these complex processes, identify biomarkers of drug sensitivity and predict the response to a drug. However, the majority of previous work has not fully utilized this temporal dimension. In these studies, the gene expression data is either considered at one time-point (before the administration of the drug) or two time-points (before and after the administration of the drug). This is clearly inadequate in modeling dynamic gene–drug interactions, especially for applications such as long-term drug therapy. In this work, we present a novel REcursive Prediction (REP) framework for drug response prediction by taking advantage of time-course gene expression data. Our goal is to predict drug response values at every stage of a long-term treatment, given the expression levels of genes collected in the previous time-points. To this end, REP employs a built-in recursive structure that exploits the intrinsic time-course nature of the data and integrates past values of drug responses for subsequent predictions. It also incorporates tensor completion that can not only alleviate the impact of noise and missing data, but also predict unseen gene expression levels (GEXs). These advantages enable REP to estimate drug response at any stage of a given treatment from some GEXs measured in the beginning of the treatment. Extensive experiments on two datasets corresponding to multiple sclerosis patients treated with interferon are included to showcase the effectiveness of REP.
more » « less- Award ID(s):
- 1704074
- NSF-PAR ID:
- 10198420
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Alzheimer’s disease (AD) is a neurogenerative condition characterized by sharp cognitive decline with no confirmed effective treatment or cure. This makes it critically important to identify the symptoms of Alzheimer’s disease in its early stages before significant cognitive deterioration has taken hold and even before any brain morphology and neuropathology are noticeable. In this study, five different multimodal deep neural networks (MDNN), with different architectures, in search of an optimal model for predicting the cognitive test scores for the Mini-Mental State Examination (MMSE) and the modified Alzheimer’s Disease Assessment Scale (ADAS-CoG13) over a span of 60 months (5 years). The multimodal data utilized to train and test the proposed models were obtained from the Alzheimer’s Disease Neuroimaging Initiative study and includes cerebrospinal fluid (CSF) levels of tau and beta-amyloid, structural measures from magnetic resonance imaging (MRI), functional and metabolic measures from positron emission tomography (PET), and cognitive scores from the neuropsychological tests (Cog). The models developed herein delve into two main issues: (1) application merits of single-task vs. multitask for predicting future cognitive scores and (2) whether time-varying input data are better suited than specific timepoints for optimizing prediction results. This model yields a high of 90.27% (SD = 1.36) prediction accuracy (correlation) at 6 months after the initial visit to a lower 79.91% (SD = 8.84) prediction accuracy at 60 months. The analysis provided is comprehensive as it determines the predictions at all other timepoints and all MDNN models include converters in the CN and MCI groups (CNc, MCIc) and all the unstable groups in the CN and MCI groups (CNun and MCIun) that reverted to CN from MCI and to MCI from AD, so as not to bias the results. The results show that the best performance is achieved by a multimodal combined single-task long short-term memory (LSTM) regressor with an input sequence length of 2 data points (2 visits, 6 months apart) augmented with a pretrained Neural Network Estimator to fill in for the missing values.more » « less
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Abstract Vertebrates respond to a diversity of stressors by rapidly elevating glucocorticoid (GC) levels. The changes in physiology and behavior triggered by this response can be crucial for surviving a variety of challenges. Yet the same process that is invaluable in coping with immediate threats can also impose substantial damage over time. In addition to the pathological effects of long-term exposure to stress hormones, even relatively brief elevations can impair the expression of a variety of behaviors and physiological processes central to fitness, including sexual behavior, parental behavior, and immune function. Therefore, the ability to rapidly and effectively terminate the short-term response to stress may be fundamental to surviving and reproducing in dynamic environments. Here we review the evidence that variation in the ability to terminate the stress response through negative feedback is an important component of stress coping capacity. We suggest that coping capacity may also be influenced by variation in the dynamic regulation of GCs—specifically, the ability to rapidly turn on and off the stress response. Most tests of the fitness effects of these traits to date have focused on organisms experiencing severe or prolonged stressors. Here we use data collected from a long-term study of tree swallows (Tachycineta bicolor) to test whether variation in negative feedback, or other measures of GC regulation, predict components of fitness in non-chronically stressed populations. We find relatively consistent, but generally weak relationships between different fitness components and the strength of negative feedback. Reproductive success was highest in individuals that both mounted a robust stress response and had strong negative feedback. We did not see consistent evidence of a relationship between negative feedback and adult or nestling survival: negative feedback was retained in the best supported models of nestling and adult survival, but in two of three survival-related analyses the intercept-only model received only slightly less support. Both negative feedback and stress-induced GC levels—but not baseline GCs—were individually repeatable. These measures of GC activity did not consistently covary across ages and life history stages, indicating that they are independently regulated. Overall, the patterns seen here are consistent with the predictions that negative feedback—and the dynamic regulation of GCs—are important components of stress coping capacity, but that the fitness benefits of having strong negative feedback during the reproductive period are likely to manifest primarily in individuals exposed to chronic or repeated stressors.
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INTRODUCTION Eukaryotes contain a highly conserved signaling pathway that becomes rapidly activated when adenosine triphosphate (ATP) levels decrease, as happens during conditions of nutrient shortage or mitochondrial dysfunction. The adenosine monophosphate (AMP)–activated protein kinase (AMPK) is activated within minutes of energetic stress and phosphorylates a limited number of substrates to biochemically rewire metabolism from an anabolic state to a catabolic state to restore metabolic homeostasis. AMPK also promotes prolonged metabolic adaptation through transcriptional changes, decreasing biosynthetic genes while increasing expression of genes promoting lysosomal and mitochondrial biogenesis. The transcription factor EB (TFEB) is a well-appreciated effector of AMPK-dependent signals, but many of the molecular details of how AMPK controls these processes remain unknown. RATIONALE The requirement of AMPK and its specific downstream targets that control aspects of the transcriptional adaptation of metabolism remain largely undefined. We performed time courses examining gene expression changes after various mitochondrial stresses in wild-type (WT) or AMPK knockout cells. We hypothesized that a previously described interacting protein of AMPK, folliculin-interacting protein 1 (FNIP1), may be involved in how AMPK promotes increases in gene expression after metabolic stress. FNIP1 forms a complex with the protein folliculin (FLCN), together acting as a guanosine triphosphate (GTP)–activating protein (GAP) for RagC. The FNIP1-FLCN complex has emerged as an amino acid sensor to the mechanistic target of rapamycin complex 1 (mTORC1), involved in how amino acids control TFEB activation. We therefore examined whether AMPK may regulate FNIP1 to dominantly control TFEB independently of amino acids. RESULTS AMPK was found to govern expression of a core set of genes after various mitochondrial stresses. Hallmark features of this response were activation of TFEB and increases in the transcription of genes specifying lysosomal and mitochondrial biogenesis. AMPK directly phosphorylated five conserved serine residues in FNIP1, suppressing the function of the FLCN-FNIP1 GAP complex, which resulted in dissociation of RagC and mTOR from the lysosome, promoting nuclear translocation of TFEB even in the presence of amino acids. FNIP1 phosphorylation was required for AMPK to activate TFEB and for subsequent increases in peroxisome proliferation–activated receptor gamma coactivator 1-alpha (PGC1α) and estrogen-related receptor alpha (ERRα) mRNAs. Cells in which the five serines in FNIP1 were mutated to alanine were unable to increase lysosomal and mitochondrial gene expression programs after treatment with mitochondrial poisons or AMPK activators despite the presence and normal regulation of all other substrates of AMPK. By contrast, neither AMPK nor its control of FNIP1 were needed for activation of TFEB after amino acid withdrawal, illustrating the specificity to energy-limited conditions. CONCLUSION Our data establish FNIP1 as the long-sought substrate of AMPK that controls TFEB translocation to the nucleus, defining AMPK phosphorylation of FNIP1 as a singular event required for increased lysosomal and mitochondrial gene expression programs after metabolic stresses. This study also illuminates the larger biological question of how mitochondrial damage triggers a temporal response of repair and replacement of damaged mitochondria: Within early hours, AMPK-FNIP1–activated TFEB induces a wave of lysosome and autophagy genes to promote degradation of damaged mitochondria, and a few hours later, TFEB–up-regulated PGC1⍺ and ERR⍺ promote expression of a second wave of genes specifying mitochondrial biogenesis. These insights open therapeutic avenues for several common diseases associated with mitochondrial dysfunction, ranging from neurodegeneration to type 2 diabetes to cancer. Mitochondrial damage activates AMPK to phosphorylate FNIP1, stimulating TFEB translocation to the nucleus and sequential waves of lysosomal and mitochondrial biogenesis. After mitochondrial damage, activated AMPK phosphorylates FNIP1 (1), causing inhibition of FLCN-FNIP1 GAP activity (2). This leads to accumulation of RagC in its GTP-bound form, causing dissociation of RagC, mTORC1, and TFEB from the lysosome (3). TFEB is therefore not phosphorylated and translocates to the nucleus, inducing transcription of lysosomal or autophagy genes, with parallel increases in NT-PGC1α mRNA (4), which, in concert with ERRα (5), subsequently induces mitochondrial biogenesis (6). CCCP, carbonyl cyanide m-chlorophenylhydrazone; CLEAR, coordinated lysosomal expression and regulation; GDP, guanosine diphosphate; P, phosphorylation. [Figure created using BioRender]more » « less
