Correction: High-resolution DNA size enrichment using a magnetic nano-platform and application in non-invasive prenatal testing.

Correction for 'High-resolution DNA size enrichment using a magnetic nano-platform and application in non-invasive prenatal testing' by Bo Zhang et al., Analyst, 2020, 145, 5733-5739, DOI: 10.1039/D0AN00813C.

Efficient detection and post-surgical monitoring of colon cancer with a multi-marker DNA methylation liquid biopsy.

Multiplex assays, involving the simultaneous use of multiple circulating tumor DNA (ctDNA) markers, can improve the performance of liquid biopsies so that they are highly predictive of cancer recurrence. We have developed a single-tube methylation-specific quantitative PCR assay (mqMSP) that uses 10 different methylation markers and is capable of quantitative analysis of plasma samples with as little as 0.05% tumor DNA. In a cohort of 179 plasma samples from colorectal cancer (CRC) patients, adenoma patients, and healthy controls, the sensitivity and specificity of the mqMSP assay were 84.9% and 83.3%, respectively. In a head-to-head comparative study, the mqMSP assay also performed better for detecting early-stage (stage I and II) and premalignant polyps than a published SEPT9 assay. In an independent longitudinal cohort of 182 plasma samples (preoperative, postoperative, and follow-up) from 82 CRC patients, the mqMSP assay detected ctDNA in 73 (89.0%) of the preoperative plasma samples. Postoperative detection of ctDNA (within 2 wk of surgery) identified 11 of the 20 recurrence patients and was associated with poorer recurrence-free survival (hazard ratio, 4.20; P = 0.0005). With subsequent longitudinal monitoring, 14 patients (70%) had detectable ctDNA before recurrence, with a median lead time of 8.0 mo earlier than seen with radiologic imaging. The mqMSP assay is cost-effective and easily implementable for routine clinical monitoring of CRC recurrence, which can lead to better patient management after surgery.

High-resolution DNA size enrichment using a magnetic nano-platform and application in non-invasive prenatal testing.

Precise DNA sizing can boost sequencing efficiency, reduce cost, improve data quality, and even allow sequencing of low-input samples, while current pervasive DNA sizing approaches are incapable of differentiating DNA fragments under 200 bp with high resolution (<20 bp). In non-invasive prenatal testing (NIPT), the size distribution of cell-free fetal DNA in maternal plasma (main peak at 143 bp) is significantly different from that of maternal cell-free DNA (main peak at 166 bp). The current pervasive workflow of NIPT and DNA sizing is unable to take advantage of this 20 bp difference, resulting in sample rejection, test inaccuracy, and restricted clinical utility. Here we report a simple, automatable, high-resolution DNA size enrichment workflow, named MiniEnrich, on a magnetic nano-platform to exploit this 20 bp size difference and to enrich fetal DNA fragments from maternal blood. Two types of magnetic nanoparticles were developed, with one able to filter high-molecular-weight DNA with high resolution and the other able to recover the remaining DNA fragments under the size threshold of interest with >95% yield. Using this method, the average fetal fraction was increased from 13% to 20% after the enrichment, as measured by plasma DNA sequencing. This approach provides a new tool for high-resolution DNA size enrichment under 200 bp, which may improve NIPT accuracy by rescuing rejected non-reportable clinical samples, and enable NIPT earlier in pregnancy. It also has the potential to improve non-invasive screening for fetal monogenic disorders, differentiate tumor-related DNA in liquid biopsy and find more applications in autoimmune disease diagnosis.

ANERGY TO SYNERGY-THE ENERGY FUELING THE RXCOVEA FRAMEWORK.

We write to introduce our novel group formed to confront some of the issues raised by the COVID-19 pandemic. Information about the group, which we named "cure COVid for Ever and for All" (RxCOVEA), its dynamic membership (changing regularly), and some of its activities-described in more technical detail for expert perusal and commentary-are available upon request.

Noninvasive diagnosis of urothelial cancer in urine using DNA hypermethylation signatures-Gender matters.

Urothelial cancer (UCa) is the most predominant cancer of the urinary tract and noninvasive diagnosis using hypermethylation signatures in urinary cells is promising. Here, we assess gender differences in a newly identified set of methylation biomarkers. UCa-associated hypermethylated sites were identified in urine of a male screening cohort (n = 24) applying Infinium-450K-methylation arrays and verified in two separate mixed-gender study groups (n = 617 in total) using mass spectrometry as an independent technique. Additionally, tissue samples (n = 56) of mixed-gender UCa and urological controls (UCt) were analyzed. The hypermethylation signature of UCa in urine was specific and sensitive across all stages and grades of UCa and independent on hematuria. Individual CpG sensitivities reached up to 81.3% at 95% specificity. Albeit similar methylation differences in tissue of both genders, differences were less pronounced in urine from women, most likely due to the frequent presence of squamous epithelial cells and leukocytes. Increased repression of methylation levels was observed at leukocyte counts ≥500/µl urine which was apparent in 30% of female and 7% of male UCa cases, further confirming the significance of the relative amounts of cancerous and noncancerous cells in urine. Our study shows that gender difference is a most relevant issue when evaluating the performance of urinary biomarkers in cancer diagnostics. In case of UCa, the clinical benefits of methylation signatures to male patients may outweigh those in females due to the general composition of women's urine. Accordingly, these markers offer a diagnostic option specifically in males to decrease the number of invasive cystoscopies.

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study we demonstrate for the first time that smoking status can be predicted using blood biochemistry and cell count results andthe recent advances in artificial intelligence (AI). By employing age-prediction models developed using supervised deep learning techniques, we found that smokers exhibited higher aging rates than nonsmokers, regardless of their cholesterol ratios and fasting glucose levels. We further used those models to quantify the acceleration of biological aging due to tobacco use. Female smokers were predicted to be twice as old as their chronological age compared to nonsmokers, whereas male smokers were predicted to be one and a half times as old as their chronological age compared to nonsmokers. Our findings suggest that deep learning analysis of routine blood tests could complement or even replace the current error-prone method of self-reporting of smoking status and could be expanded to assess the effect of other lifestyle and environmental factors on aging.

miR-34a directly targets tRNAiMet precursors and affects cellular proliferation, cell cycle, and apoptosis.

It remains unknown whether microRNA (miRNA/miR) can target transfer RNA (tRNA) molecules. Here we provide evidence that miR-34a physically interacts with and functionally targets tRNAiMet precursors in both in vitro pulldown and Argonaute 2 (AGO2) cleavage assays. We find that miR-34a suppresses breast carcinogenesis, at least in part by lowering the levels of tRNAiMet through AGO2-mediated repression, consequently inhibiting the proliferation of breast cancer cells and inducing cell cycle arrest and apoptosis. Moreover, miR-34a expression is negatively correlated with tRNAiMet levels in cancer cell lines. Furthermore, we find that tRNAiMet knockdown also reduces cell proliferation while inducing cell cycle arrest and apoptosis. Conversely, ectopic expression of tRNAiMet promotes cell proliferation, inhibits apoptosis, and accelerates the S/G2 transition. Moreover, the enforced expression of modified tRNAiMet completely restores the phenotypic changes induced by miR-34a. Our results demonstrate that miR-34a directly targets tRNAiMet precursors via AGO2-mediated cleavage, and that tRNAiMet functions as an oncogene, potentially representing a target molecule for therapeutic intervention.

Deuterium-reinforced linoleic acid lowers lipid peroxidation and mitigates cognitive impairment in the Q140 knock in mouse model of Huntington's disease.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease which has no effective treatment and is characterized by psychiatric disorders, motor alterations, and dementia, with the cognitive deficits representing a devastating aspect of the disorder. Oxidative stress and elevated levels of lipid peroxidation (LPO) products are found in mouse models and patients with HD, suggesting that strategies to reduce LPO may be beneficial in HD. In contrast with traditional antioxidants, substituting hydrogen with deuterium at bis-allylic sites in polyunsaturated fatty acids (D-PUFA) decreases the rate-limiting initiation step of PUFA autoxidation, a strategy that has shown benefits in other neurodegenerative diseases. Here, we investigated the effect of D-PUFA treatment in a knock-in mouse model of HD (Q140) which presents motor deficits and neuropathology from a few months of age, and progressive cognitive decline. Q140 knock-in mice were fed a diet containing either D- or H-PUFAs for 5 months starting at 1 month of age. D-PUFA treatment significantly decreased F2 -isoprostanes in the striatum by approximately 80% as compared to H-PUFA treatment and improved performance in novel object recognition tests, without significantly changing motor deficits or huntingtin aggregation. Therefore, D-PUFA administration represents a promising new strategy to broadly reduce rates of LPO, and may be useful in improving a subset of the core deficits in HD.

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data.

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

Surface EMG activity during REM sleep in Parkinson's disease correlates with disease severity.

OBJECTIVES: Over 40% of individuals with Parkinson's disease (PD) have rapid eye movement sleep behavior disorder (RBD). This is associated with excessive sustained (tonic) or intermittent (phasic) muscle activity instead of the muscle atonia normally seen during REM sleep. We examined characteristics of manually-quantitated surface EMG activity in PD to ascertain whether the extent of muscle activity during REM sleep is associated with specific clinical features and measures of disease severity. METHODS: In a convenience sample of outpatients with idiopathic PD, REM sleep behavior disorder was diagnosed based on clinical history and polysomnogram, and severity was measured using the RBD sleep questionnaire. Surface EMG activity in the mentalis, extensor muscle group of the forearms, and anterior tibialis was manually quantitated. Percentage of REM time with excessive tonic or phasic muscle activity was calculated and compared across PD and RBD characteristics. RESULTS: Among 65 patients, 31 had confirmed RBD. In univariate analyses, higher amounts of surface EMG activity were associated with longer PD disease duration (srho = 0.34; p = 0.006) and greater disease severity (p < 0.001). In a multivariate regression model, surface EMG activity was significantly associated with RBD severity (p < 0.001) after adjustment for age, PD disease duration, PD severity and co-morbid sleep abnormalities. CONCLUSION: Surface EMG activity during REM sleep was associated with severity of both PD and RBD. This measure may be useful as a PD biomarker and, if confirmed, may aid in determining which PD patients warrant treatment for their dream enactment to reduce risk of injury.

Human-specific endogenous retroviral insert serves as an enhancer for the schizophrenia-linked gene PRODH.

Using a systematic, whole-genome analysis of enhancer activity of human-specific endogenous retroviral inserts (hsERVs), we identified an element, hsERVPRODH, that acts as a tissue-specific enhancer for the PRODH gene, which is required for proper CNS functioning. PRODH is one of the candidate genes for susceptibility to schizophrenia and other neurological disorders. It codes for a proline dehydrogenase enzyme, which catalyses the first step of proline catabolism and most likely is involved in neuromediator synthesis in the CNS. We investigated the mechanisms that regulate hsERVPRODH enhancer activity. We showed that the hsERVPRODH enhancer and the internal CpG island of PRODH synergistically activate its promoter. The enhancer activity of hsERVPRODH is regulated by methylation, and in an undermethylated state it can up-regulate PRODH expression in the hippocampus. The mechanism of hsERVPRODH enhancer activity involves the binding of the transcription factor SOX2, whch is preferentially expressed in hippocampus. We propose that the interaction of hsERVPRODH and PRODH may have contributed to human CNS evolution.

From personalized medicine to personalized science: uniting science and medicine for patient-driven, goal-oriented research.

We developed a new model for initiating, coordinating, funding, and managing biomedical research projects. The concept involves engaging the patients with chronic conditions with no known cures into goal-oriented research activities. In this model, the patient seeks the help of a research organization to bring together a multidisciplinary team of research scientists and physicians to initiate research projects using the patient's grant funding, samples, as well as the management expertise. This model may be of interest to other research institutions because it has many benefits, including new sources of private research funding, when government funding is getting scarce, motivating scientists and physicians to work closely together on goal- and patient-oriented research projects, and using patients' management skills.

Detection of hepatitis C virus transmission by use of DNA mass spectrometry.

The molecular detection of transmission of rapidly mutating pathogens such as hepatitis C virus (HCV) is commonly achieved by assessing the genetic relatedness of strains among infected patients. We describe the development of a novel mass spectrometry (MS)-based approach to identify HCV transmission. MS was used to detect products of base-specific cleavage of RNA molecules obtained from HCV polymerase chain reaction fragments. The MS-peak profiles were found to reflect variation in the HCV genomic sequence and the intrahost composition of the HCV population. Serum specimens originating from 60 case patients from 14 epidemiologically confirmed outbreaks and 25 unrelated controls were tested. Neighbor-joining trees constructed using MS-peak profile-based Hamming distances showed 100% accuracy, and linkage networks constructed using a threshold established from the Hamming distances between epidemiologically unrelated cases showed 100% sensitivity and 99.93% specificity in transmission detection. This MS-based approach is rapid, robust, reproducible, cost-effective, and applicable to investigating transmissions of other pathogens.

Small amounts of isotope-reinforced polyunsaturated fatty acids suppress lipid autoxidation.

Polyunsaturated fatty acids (PUFAs) undergo autoxidation and generate reactive carbonyl compounds that are toxic to cells and associated with apoptotic cell death, age-related neurodegenerative diseases, and atherosclerosis. PUFA autoxidation is initiated by the abstraction of bis-allylic hydrogen atoms. Replacement of the bis-allylic hydrogen atoms with deuterium atoms (termed site-specific isotope-reinforcement) arrests PUFA autoxidation due to the isotope effect. Kinetic competition experiments show that the kinetic isotope effect for the propagation rate constant of Lin autoxidation compared to that of 11,11-D(2)-Lin is 12.8 ± 0.6. We investigate the effects of different isotope-reinforced PUFAs and natural PUFAs on the viability of coenzyme Q-deficient Saccharomyces cerevisiae coq mutants and wild-type yeast subjected to copper stress. Cells treated with a C11-BODIPY fluorescent probe to monitor lipid oxidation products show that lipid peroxidation precedes the loss of viability due to H-PUFA toxicity. We show that replacement of just one bis-allylic hydrogen atom with deuterium is sufficient to arrest lipid autoxidation. In contrast, PUFAs reinforced with two deuterium atoms at mono-allylic sites remain susceptible to autoxidation. Surprisingly, yeast treated with a mixture of approximately 20%:80% isotope-reinforced D-PUFA:natural H-PUFA are protected from lipid autoxidation-mediated cell killing. The findings reported here show that inclusion of only a small fraction of PUFAs deuterated at the bis-allylic sites is sufficient to profoundly inhibit the chain reaction of nondeuterated PUFAs in yeast.

Company profile: Sequenom, Inc.

There is broad acceptance in both the research and clinical communities that the age of personalized medicine is rapidly approaching. Numerous examples of biomarkers (and tests based on those biomarkers) have been shown to be relevant to clinically important phenotypes. Sequenom, Inc. is at the forefront of this molecular medicine revolution. The company provides genetic analysis instrumentation and reagents to the clinical and research communities. These products are being used for clinical validation of relevant biomarkers as well as for development of diagnostic tests based on those biomarkers.

Genetic switchboard for synthetic biology applications.

A key next step in synthetic biology is to combine simple circuits into higher-order systems. In this work, we expanded our synthetic riboregulation platform into a genetic switchboard that independently controls the expression of multiple genes in parallel. First, we designed and characterized riboregulator variants to complete the foundation of the genetic switchboard; then we constructed the switchboard sensor, a testing platform that reported on quorum-signaling molecules, DNA damage, iron starvation, and extracellular magnesium concentration in single cells. As a demonstration of the biotechnological potential of our synthetic device, we built a metabolism switchboard that regulated four metabolic genes, pgi, zwf, edd, and gnd, to control carbon flow through three Escherichia coli glucose-utilization pathways: the Embden-Meyerhof, Entner-Doudoroff, and pentose phosphate pathways. We provide direct evidence for switchboard-mediated shunting of metabolic flux by measuring mRNA levels of the riboregulated genes, shifts in the activities of the relevant enzymes and pathways, and targeted changes to the E. coli metabolome. The design, testing, and implementation of the genetic switchboard illustrate the successful construction of a higher-order system that can be used for a broad range of practical applications in synthetic biology and biotechnology.

Isotopic reinforcement of essential polyunsaturated fatty acids diminishes nigrostriatal degeneration in a mouse model of Parkinson's disease.

Oxidative damage of membrane polyunsaturated fatty acids (PUFA) is thought to play a major role in mitochondrial dysfunction related to Parkinson's disease (PD). The toxic products formed by PUFA oxidation inflict further damage on cellular components and contribute to neuronal degeneration. Here, we tested the hypothesis that isotopic reinforcement, by deuteration of the bisallylic sites most susceptible to oxidation in PUFA may provide at least partial protection against nigrostriatal injury in a mouse model of oxidative stress and cell death, the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model. Mice were fed a fat-free diet supplemented with saturated acids, oleic acid and essential PUFA: either normal, hydrogenated linoleic (LA, 18:2n-6) and α-linolenic (ALA, 18:3n-3) or deuterated 11,11-D2-LA and 11,11,14,14-D4-ALA in a ratio of 1:1 (to a total of 10% mass fat) for 6 days; each group was divided into two cohorts receiving either MPTP or saline and then continued on respective diets for 6 days. Brain homogenates from mice receiving deuterated PUFA (D-PUFA) vs. hydrogenated PUFA (H-PUFA) demonstrated a significant incorporation of deuterium as measured by isotope ratio mass-spectrometry. Following MPTP exposure, mice fed H-PUFA revealed 78.7% striatal dopamine (DA) depletion compared to a 46.8% reduction in the D-PUFA cohort (as compared to their respective saline-treated controls), indicating a significant improvement in DA concentration with D-PUFA. Similarly, higher levels of the DA metabolite 3,4-dihydroxyphenylacetic acid (DOPAC) were detected in MPTP-exposure mice administered D-PUFA; however, saline-treated mice revealed no change in DA or DOPAC levels. Western blot analyses of tyrosine hydroxylase (TH) confirmed neuroprotection with D-PUFA, as striatal homogenates showed higher levels of TH immunoreactivity in D-PUFA (88.5% control) vs. H-PUFA (50.4% control) in the MPTP-treated cohorts. In the substantia nigra, a significant improvement was noted in the number of nigral dopaminergic neurons following MPTP exposure in the D-PUFA (79.5% control) vs. H-PUFA (58.8% control) mice using unbiased stereological cell counting. Taken together, these findings indicate that dietary isotopic reinforcement with D-PUFA partially protects against nigrostriatal damage from oxidative injury elicited by MPTP in mice.