Parallel Picoliter RT-PCR Assays Using Microfluidics

The development of microfluidic tools for high-throughput nucleic acid analysis has become a burgeoning area of research in the post-genome era. Here, we have developed a microfluidic chip to perform 72 parallel 450-pL RT-PCRs. We took advantage of Taqman hydrolysis probe chemistry to detect RNA templates as low as 34 copies. The device and method presented here may enable highly parallel single cell gene expression analysis

A microfluidic processor for gene expression profiling of single human embryonic stem cells

The gene expression of human embryonic stem cells (hESC) is a critical aspect for understanding the normal and pathological development of human cells and tissues. Current bulk gene expression assays rely on RNA extracted from cell and tissue samples with various degree of cellular heterogeneity. These cell population averaging data are difficult to interpret, especially for the purpose of understanding the regulatory relationship of genes in the earliest phases of development and differentiation of individual cells. Here, we report a microfluidic approach that can extract total mRNA from individual single-cells and synthesize cDNA on the same device with high mRNA-to-cDNA efficiency. This feature makes large-scale single-cell gene expression profiling possible. Using this microfluidic device, we measured the absolute numbers of mRNA molecules of three genes (B2M, Nodal and Fzd4) in a single hESC. Our results indicate that gene expression data measured from cDNA of a cell population is not a good representation of the expression levels in individual single cells. Within the G0/G1 phase pluripotent hESC population, some individual cells did not express all of the 3 interrogated genes in detectable levels. Consequently, the relative expression levels, which are broadly used in gene expression studies, are very different between measurements from population cDNA and single-cell cDNA. The results underscore the importance of discrete single-cell analysis, and the advantages of a microfluidic approach in stem cell gene expression studies

MRI-based classification of IDH mutation and 1p/19q codeletion status of gliomas using a 2.5D hybrid multi-task convolutional neural network

Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status are important prognostic markers for glioma. Currently, they are determined using invasive procedures. Our goal was to develop artificial intelligence-based methods to non-invasively determine these molecular alterations from MRI. For this purpose, pre-operative MRI scans of 2648 patients with gliomas (grade II-IV) were collected from Washington University School of Medicine (WUSM; n = 835) and publicly available datasets viz. Brain Tumor Segmentation (BraTS; n = 378), LGG 1p/19q (n = 159), Ivy Glioblastoma Atlas Project (Ivy GAP; n = 41), The Cancer Genome Atlas (TCGA; n = 461), and the Erasmus Glioma Database (EGD; n = 774). A 2.5D hybrid convolutional neural network was proposed to simultaneously localize the tumor and classify its molecular status by leveraging imaging features from MR scans and prior knowledge features from clinical records and tumor location. The models were tested on one internal (TCGA) and two external (WUSM and EGD) test sets. For IDH, the best-performing model achieved areas under the receiver operating characteristic (AUROC) of 0.925, 0.874, 0.933 and areas under the precision-recall curves (AUPRC) of 0.899, 0.702, 0.853 on the internal, WUSM, and EGD test sets, respectively. For 1p/19q, the best model achieved AUROCs of 0.782, 0.754, 0.842, and AUPRCs of 0.588, 0.713, 0.782, on those three data-splits, respectively. The high accuracy of the model on unseen data showcases its generalization capabilities and suggests its potential to perform a 'virtual biopsy' for tailoring treatment planning and overall clinical management of gliomas

On the role of the corpus callosum in interhemispheric functional connectivity in humans

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity

The Effects of Physical Activity on Markers of Adipose Inflammation during Weight Cycling

Weight loss using diet and exercise are the main treatment strategies for obesity; however, weight loss is rarely maintained resulting in weight regain or weight cycling. Obesity is associated with chronic low-grade inflammation resulting in the release of adipokines and activation of macrophages (M1) accelerating the development of insulin resistance. In contrast, the M2 macrophage phenotype is characterized by blocking inflammatory responses and promoting tissue repair. Despite the effectiveness of exercise on preventing comorbidities of obesity during weight-loss, the influence of physical activity during weight cycling on markers of adipose inflammation remains unclear. Purpose: The purpose of this study was to determine the role of physical activity on the expression of inflammatory markers in adipose tissue during weight cycling. Methods: Male C57BL/6 mice were randomly assigned to one of three groups for 28 weeks: a high-fat diet obese control (HFD; 60% kcal from fat), an alternating high-low-high fat diet group (Diet; 60%/10%/60% kcal from fat) to simulate weight cycling, or a diet-matched weight cycling group that had unrestricted access to running wheels (Diet+PA). After weight regain, MCP-1, CD11c, CD163, F4/80, TLR4, and TNFα mRNA levels were quantified in perigonadal adipose tissue using qRT-PCR. A one-way ANOVA was used to identify significant differences between groups with significance set at PWeight cycling without physical activity resulted in obesity and insulin resistance when compared to HFD obese controls. Interestingly, compared to the HFD control group, the Diet group demonstrated significantly greater expression of F4/80 (+50%), CD11c (+113%), TLR4 (+77%), and TNFα (+72%) mRNA, which may represent greater macrophage infiltration and M1 macrophage polarization. Physical activity during weight cycling resulted in lower weight regain compared to both HFD and Diet groups; however, mice still developed insulin resistance and increased expression of TLR4 (+76%), TNFα (+94%), and CD11c (+58%) suggesting increased M1 macrophage activation when compared to the HFD group. Conclusions: The data presented suggests weight cycling may accelerate the development of adipose dysfunction, and unrestricted physical activity appears to have minimal effects on the negative inflammatory effects of weight cycling

The Effects of Physical Activity on Markers of Hepatic Lipid Metabolism during Weight Cycling

Non-alcoholic fatty liver disease (NAFLD) has emerged as the leading cause of liver disease and develops when the rate of hepatic triglyceride formation exceeds the rate of disposal. Weight loss is often prescribed to treat NAFLD; however, only one in six obese or overweight individuals who lose weight through diet are successful at maintaining weight loss resulting in weight regain (i.e., weight cycling). Purpose: To determine the effect of physical activity on the prevention of hepatic steatosis and expression of lipogenic genes during weight cycling. Methods: To induce obesity, male C57BL/6 mice were fed a 60% fat diet for 10-weeks. Following weight gain, mice were randomly assigned to a 10% fat diet either with (Diet+PA) or without (Diet) physical activity to induce weight loss for 8 weeks. Physical activity consisted of unrestricted access to running wheels. Following weight loss, the Diet and Diet+PA groups were switched back to a 60% fat diet for 10 weeks to cause weight regain. The Diet+PA had continued access to physical activity during weight regain. Age-matched lean and obese control mice were fed either a 10% fat diet (LF) or 60% fat diet (HF) for the entire 28 weeks of the study. Significant differences (P\u3c0.05) between groups were identified by one-way ANOVA. Results: Following weight regain, body mass of the Diet+PA was significantly lower than the HF (47.8 vs. 55.3 g) and Diet (47.8 vs. 53.9 g). No significant difference in body mass was observed between Diet and HF groups. The Diet+PA had significantly lower plasma cholesterol levels compared to HF (230.5 vs. 254.5 mg/dL) and Diet (230.5 vs. 271.9 mg/dL). In addition, the Diet+PA group had significantly lower total hepatic lipid (23.2 vs. 26.5%) when compared with Diet, which was associated with 60%, 50%, and 40% lower expression of lipogenic genes Fasn, Srebp1c, and Chrebp, respectively. No difference was noted between Diet and Diet+PA for the expression of lipogenic genes Scd1 and Acc1. Conclusions: These data suggests that the continued physical activity during weight cycling resulted in lower weight regain and reduced the accumulation of hepatic lipid by decreased de novo lipogenesis. Overall, the reduced expression of lipogenic related genes might point to a potential protective mechanism that physical activity has on the development of NAFLD during weight cycling

Machine learning analytics of resting-state functional connectivity predicts survival outcomes of glioblastoma multiforme patients

Glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy. Due to its poor prognosis with currently available treatments, there is a pressing need for easily accessible, non-invasive techniques to help inform pre-treatment planning, patient counseling, and improve outcomes. In this study we determined the feasibility of resting-state functional connectivity (rsFC) to classify GBM patients into short-term and long-term survival groups with respect to reported median survival (14.6 months). We used a support vector machine with rsFC between regions of interest as predictive features. We employed a novel hybrid feature selection method whereby features were first filtered using correlations between rsFC and OS, and then using the established method of recursive feature elimination (RFE) to select the optimal feature subset. Leave-one-subject-out cross-validation evaluated the performance of models. Classification between short- and long-term survival accuracy was 71.9%. Sensitivity and specificity were 77.1 and 65.5%, respectively. The area under the receiver operating characteristic curve was 0.752 (95% CI, 0.62-0.88). These findings suggest that highly specific features of rsFC may predict GBM survival. Taken together, the findings of this study support that resting-state fMRI and machine learning analytics could enable a radiomic biomarker for GBM, augmenting care and planning for individual patients

Microfluidic Single-Cell mRNA Isolation and Analysis

Single-cell gene expression analysis holds great promise for studying diverse biological systems, but methodology to process these precious samples in a reproducible, quantitative, and parallel fashion remains challenging. Here, we utilize microfluidics to isolate picogram and subpicogram mRNA templates, as well as to synthesize cDNA from these templates. We demonstrate single-cell mRNA isolation and cDNA synthesis, provide quantitative calibrations for each step in the process, and measure gene expression in individual cells. The techniques presented here form the foundation for highly parallel single-cell gene expression studies

Parallel Picoliter RT-PCR Assays Using Microfluidics

The development of microfluidic tools for high-throughput nucleic acid analysis has become a burgeoning area of research in the post-genome era. Here, we have developed a microfluidic chip to perform 72 parallel 450-pL RT-PCRs. We took advantage of Taqman hydrolysis probe chemistry to detect RNA templates as low as 34 copies. The device and method presented here may enable highly parallel single cell gene expression analysis

Modulation of the Intestinal Microbiota Alters Colitis-Associated Colorectal Cancer Susceptibility

It is well established that the intestinal microbiota plays a key role in the pathogenesis of Crohn's disease (CD) and ulcerative colitis (UC) collectively referred to as inflammatory bowel disease (IBD). Epidemiological studies have provided strong evidence that IBD patients bear increased risk for the development of colorectal cancer (CRC). However, the impact of the microbiota on the development of colitis-associated cancer (CAC) remains largely unknown. In this study, we established a new model of CAC using azoxymethane (AOM)-exposed, conventionalized-Il10−/− mice and have explored the contribution of the host intestinal microbiota and MyD88 signaling to the development of CAC. We show that 8/13 (62%) of AOM-Il10−/− mice developed colon tumors compared to only 3/15 (20%) of AOM- wild-type (WT) mice. Conventionalized AOM-Il10−/− mice developed spontaneous colitis and colorectal carcinomas while AOM-WT mice were colitis-free and developed only rare adenomas. Importantly, tumor multiplicity directly correlated with the presence of colitis. Il10−/− mice mono-associated with the mildly colitogenic bacterium Bacteroides vulgatus displayed significantly reduced colitis and colorectal tumor multiplicity compared to Il10−/− mice. Germ-free AOM-treated Il10−/− mice showed normal colon histology and were devoid of tumors. Il10−/−; Myd88−/− mice treated with AOM displayed reduced expression of Il12p40 and Tnfα mRNA and showed no signs of tumor development. We present the first direct demonstration that manipulation of the intestinal microbiota alters the development of CAC. The TLR/MyD88 pathway is essential for microbiota-induced development of CAC. Unlike findings obtained using the AOM/DSS model, we demonstrate that the severity of chronic colitis directly correlates to colorectal tumor development and that bacterial-induced inflammation drives progression from adenoma to invasive carcinoma