poolMC: smart pooling of mRNA samples in microarray experiments

MultiplexMS: A Mass Spectrometry-Based Multiplexing Strategy for Ultra-High-Throughput Analysis of Complex Mixtures

High-throughput chemical analysis of natural product mixtures lags behind developments in genome sequencing technologies and laboratory automation, leading to a disconnect between library-scale chemical and biological profiling that limits new molecule discovery. Here, we report a new orthogonal sample multiplexing strategy that can increase mass spectrometry-based profiling up to 30-fold over traditional methods. Profiled pooled samples undergo subsequent computational deconvolution to reconstruct peak lists for each sample in the set. We validated this approach using in silico experiments and demonstrated a high assignment precision (>97%) for large, pooled samples (r = 30), particularly for infrequently occurring metabolites of relevance in drug discovery applications. Requiring only 5% of the previously required MS acquisition time, this approach was repeated in a recent biological activity profiling study on 925 natural product extracts, leading to the rediscovery of all previously reported bioactive metabolites. This new method is compatible with MS data from any instrument vendor and is supported by an open-source software package: https://github.com/liningtonlab/MultiplexMS.

Considerations for Group Testing: A Practical Approach for the Clinical Laboratory

Group testing, also known as pooled sample testing, was first proposed by Robert Dorfman in 1943. While sample pooling has been widely practiced in blood-banking, it is traditionally seen as anathema for clinical laboratories. However, the ongoing COVID-19 pandemic has re-ignited interest for group testing among clinical laboratories to mitigate supply shortages. We propose five criteria to assess the suitability of an analyte for pooled sample testing in general and outline a practical approach that a clinical laboratory may use to implement pooled testing for SARS-CoV-2 PCR testing. The five criteria we propose are: (1) the analyte concentrations in the diseased persons should be at least one order of magnitude (10 times) higher than in healthy persons; (2) sample dilution should not overly reduce clinical sensitivity; (3) the current prevalence must be sufficiently low for the number of samples pooled for the specific protocol; (4) there is no requirement for a fast turnaround time; and (5) there is an imperative need for resource rationing to maximise public health outcomes. The five key steps we suggest for a successful implementation are: (1) determination of when pooling takes place (pre-pre analytical, pre-analytical, analytical); (2) validation of the pooling protocol; (3) ensuring an adequate infrastructure and archival system; (4) configuration of the laboratory information system; and (5) staff training. While pool testing is not a panacea to overcome reagent shortage, it may allow broader access to testing but at the cost of reduction in sensitivity and increased turnaround time.

Early synergistic interactions between the HPV16‑E7 oncoprotein and 17β-oestradiol for repressing the expression of Granzyme B in a cervical cancer model

Although high-risk human papillomavirus (HR‑HPV) infection has a prominent role in the aetiology of cervical cancer (CC), sex steroid hormones may also be involved in this process; however, the cooperation between oestrogen and HR‑HPV in the early stages of cervical carcinogenesis is poorly understood. Since 17β-oestradiol (E2) and the HPV type 16‑E7 oncoprotein induce CC in transgenic mice, a microarray analysis was performed in the present study to generate global gene expression profiles from 2‑month‑old FVB (non‑transgenic) and K14E7 (transgenic) mice who were left untreated or were treated for 1 month with E2. Upregulation of cancer-related genes that have not been previously reported in the context of CC, including glycerophosphodiester phosphodiesterase domain containing 3, interleukin 1 receptor type II, natriuretic peptide type C, MGAT4 family member C, lecithin-retinol acyltransferase (phosphatidylcholine-retinol-O-acyltransferase) and glucoside xylosyltransferase 2, was observed. Notably, upregulation of the serine (or cysteine) peptidase inhibitor clade B member 9 gene and downregulation of the Granzyme gene family were observed; the repression of the Granzyme B pathway may be a novel mechanism of immune evasion by cancer cells. The present results provide the basis for further studies on early biomarkers of CC risk and synergistic interactions between HR‑HPV and oestrogen.

pH Stress-Induced Cooperation between Rhodococcus ruber YYL and Bacillus cereus MLY1 in Biodegradation of Tetrahydrofuran

Microbial consortia consisting of cooperational strains exhibit biodegradation performance superior to that of single microbial strains and improved remediation efficiency by relieving the environmental stress. Tetrahydrofuran (THF), a universal solvent widely used in chemical and pharmaceutical synthesis, significantly affects the environment. As a refractory pollutant, THF can be degraded by some microbial strains under suitable conditions. There are often a variety of stresses, especially pH stress, that inhibit the THF-degradation efficiency of microbial consortia. Therefore, it is necessary to study the molecular mechanisms of microbial cooperational degradation of THF. In this study, under conditions of low pH (initial pH = 7.0) stress, a synergistic promotion of the THF degradation capability of the strain Rhodococcus ruber YYL was found in the presence of a non-THF degrading strain Bacillus cereus MLY1. Metatranscriptome analysis revealed that the low pH stress induced the strain YYL to up-regulate the genes involved in anti-oxidation, mutation, steroid and bile acid metabolism, and translation, while simultaneously down-regulating the genes involved in ATP production. In the co-culture system, strain MLY1 provides fatty acids, ATP, and amino acids for strain YYL in response to low pH stress during THF degradation. In return, YYL shares the metabolic intermediates of THF with MLY1 as carbon sources. This study provides the preliminary mechanism to understand how microbial consortia improve the degradation efficiency of refractory furan pollutants under environmental stress conditions.

Behavioral and omics analyses study on potential involvement of dipeptide balenine through supplementation in diet of senescence-accelerated mouse prone 8

This study investigates effects of dipeptide balenine, as a major component of whale meat extract (hereafter, WME), supplementation on senescence-accelerated mouse prone 8 (SAMP8), an Alzheimer's disease (AD) model at level of learning and memory formation and brain expression profiles genome-wide in brain. Mice fed experimental balenine (+ WME) supplemented diet for 26 weeks were subjected to four behavioral tests – open field, Y-maze, novel object recognition, and water-filled multiple T-maze – to examine effects on learning and memory. Brain transcriptome of SAMP8 mice-fed the WME diet over control low-safflower oil (LSO) diet-fed mice was delineated on a 4 × 44 K mouse whole genome DNA microarray chip. Results revealed the WME diet not only induced improvements in the learning and memory formation but also positively modulated changes in the brain of the SAMP8 mouse; the gene inventories are publically available for analysis by the scientific community. Interestingly, the SAMP8 mouse model presented many genetic characteristics of AD, and numerous novel molecules (Slc2a5, Treh, Fbp1, Aldob, Ppp1r1a, DNase1, Agxt2l1, Cyp2e1, Acsm1, Acsm2, and Pah) were revealed over the SAMR1 (senescence-accelerated mouse resistant 1) mouse, to be oppositely regulated/recovered under the balenine (+ WME) supplemented diet regime by DNA microarray and bioinformatics analyses. Our present study demonstrates an experimental strategy to understand the effects of dipeptide balenine, prominetly contained in meat diet, on SAMP8, providing new insight into whole brain transcriptome changes genome-wide. The gene expression data has been deposited into the Gene Expression Omnibus (GEO): GSE76459. The data will be a valuable resource in examining the effects of natural products, and which could also serve as a human model for further functional analysis and investigation.

Unraveling the Rat Intestine, Spleen and Liver Genome-Wide Transcriptome after the Oral Administration of Lavender Oil by a Two-Color Dye-Swap DNA Microarray Approach

The use of lavender oil (LO)--a commonly, used oil in aromatherapy, with well-defined volatile components linalool and linalyl acetate--in non-traditional medicine is increasing globally. To understand and demonstrate the potential positive effects of LO on the body, we have established an animal model in this current study, investigating the orally administered LO effects genome wide in the rat small intestine, spleen, and liver. The rats were administered LO at 5 mg/kg (usual therapeutic dose in humans) followed by the screening of differentially expressed genes in the tissues, using a 4×44-K whole-genome rat chip (Agilent microarray platform; Agilent Technologies, Palo Alto, CA, USA) in conjunction with a dye-swap approach, a novelty of this study. Fourteen days after LO treatment and compared with a control group (sham), a total of 156 and 154 up (≧ 1.5-fold)- and down (≦ 0.75-fold)-regulated genes, 174 and 66 up- (≧ 1.5-fold)- and down (≦ 0.75-fold)-regulated genes, and 222 and 322 up- (≧ 1.5-fold)- and down (≦ 0.75-fold)-regulated genes showed differential expression at the mRNA level in the small intestine, spleen and liver, respectively. The reverse transcription-polymerase chain reaction (RT-PCR) validation of highly up- and down-regulated genes confirmed the regulation of the Papd4, Lrp1b, Alb, Cyr61, Cyp2c, and Cxcl1 genes by LO as examples in these tissues. Using bioinformatics, including Ingenuity Pathway Analysis (IPA), differentially expressed genes were functionally categorized by their Gene Ontology (GO) and biological function and network analysis, revealing their diverse functions and potential roles in LO-mediated effects in rat. Further IPA analysis in particular unraveled the presence of novel genes, such as Papd4, Or8k5, Gprc5b, Taar5, Trpc6, Pld2 and Onecut3 (up-regulated top molecules) and Tnf, Slc45a4, Slc25a23 and Samt4 (down-regulated top molecules), to be influenced by LO treatment in the small intestine, spleen and liver, respectively. These results are the first such inventory of genes that are affected by lavender essential oil (LO) in an animal model, forming the basis for further in-depth bioinformatics and functional analyses and investigation.

Proteomic analysis and qRT-PCR verification of temperature response to Arthrospira (Spirulina) platensis

Arthrospira (Spirulina) platensis (ASP) is a representative filamentous, non-N2-fixing cyanobacterium that has great potential to enhance the food supply and possesses several valuable physiological features. ASP tolerates high and low temperatures along with highly alkaline and salty environments, and can strongly resist oxidation and irradiation. Based on genomic sequencing of ASP, we compared the protein expression profiles of this organism under different temperature conditions (15°C, 35°Cand 45°C) using 2-DE and peptide mass fingerprinting techniques. A total of 122 proteins having a significant differential expression response to temperature were retrieved. Of the positively expressed proteins, the homologies of 116 ASP proteins were found in Arthrospira (81 proteins in Arthrospira platensis str. Paraca and 35 in Arthrospira maxima CS-328). The other 6 proteins have high homology with other microorganisms. We classified the 122 differentially expressed positive proteins into 14 functions using the COG database, and characterized their respective KEGG metabolism pathways. The results demonstrated that these differentially expressed proteins are mainly involved in post-translational modification (protein turnover, chaperones), energy metabolism (photosynthesis, respiratory electron transport), translation (ribosomal structure and biogenesis) and carbohydrate transport and metabolism. Others proteins were related to amino acid transport and metabolism, cell envelope biogenesis, coenzyme metabolism and signal transduction mechanisms. Results implied that these proteins can perform predictable roles in rendering ASP resistance against low and high temperatures. Subsequently, we determined the transcription level of 38 genes in vivo in response to temperature and identified them by qRT-PCR. We found that the 26 differentially expressed proteins, representing 68.4% of the total target genes, maintained consistency between transcription and translation levels. The remaining 12 genes showed inconsistent protein expression with transcription level and accounted for 31.6% of the total target genes.

Designing pooling systems for noisy high-throughput protein-protein interaction experiments using boolean compressed sensing

Group testing, also known as pooling, is a common technique used in high-throughput experiments in molecular biology to significantly reduce the number of tests required to identify rare biological interactions while correcting for experimental noise. Central to the group testing problem are 1) a pooling design that lays out how items are grouped together into pools for testing and 2) a decoder that interprets the results of the tested pools, identifying the active compounds. In this work, we take advantage of decoder guarantees from the field of compressed sensing (CS) to address the problem of efficient and reliable detection of biological interaction in noisy high-throughput experiments. We also use efficient combinatorial algorithms from group testing as well as established measurement matrices from CS to create pooling designs. First, we formulate the group testing problem in terms of a Boolean CS framework. We then propose a low-complexity l1-norm decoder to interpret pooling test results and identify active compounds. We demonstrate the robustness of the proposed l1-norm decoder in simulated experiments with false-positive and false-negative error rates typical of high-throughput experiments. When benchmarked against the current state-of-the-art methods, the proposed l1-norm decoder provides superior error correction for the majority of the cases considered while being notably faster computationally. Additionally, we test the performance of the l1-norm decoder against a real experimental data set, where 12,675 prey proteins were screened against 12 bait proteins. Lastly, we study the impact of different sparse pooling design matrices on decoder performance and show that the shifted transversal design (STD) is the most suitable among the pooling designs surveyed for biological applications of CS.

Association of a single-nucleotide polymorphism within the miR-146a gene with susceptibility for acute-on-chronic hepatitis B liver failure

Excessive activation of innate immune response contributes to the pathogenesis of acute-on-chronic hepatitis B liver failure (ACLF-HBV). miR-146a was recently found to be implicated in the regulation of innate immunity. In this study, we explored the biological significance of a single-nucleotide polymorphism (rs2910164) within the miR-146a gene in the risk of acquiring ACLF-HBV. We completed a hospital-based case-control study including 717 cases of HBV-infected patients--251 cases of ACLF-HBV and 466 cases of chronic hepatitis B. Whole blood samples were collected for isolation of DNA and peripheral blood mononuclear cells (PBMCs). The association between genotypes and risk of ACLF-HBV was analyzed by multivariate unconditional logistic regression, with adjustment for sex and age. Our results showed that the GG homozygote was a protective genotype in terms of susceptibility to ACLF-HBV, with odds ratio = 0.496, 95 % confidence interval = 0.309-0.797, P = 0.004 compared with CC+GC genotypes. The amount of mature miR-146a in PBMCs was significantly higher in the GG homozygote group than those in the CC and CG genotype groups of ACLF-HBV patients. The GG genotype group also represented lower serum level of TNF-α and higher survival rate (follow-up period = 4 months). In conclusion, The GG genotype within the pre-miR-146a is reversely associated with susceptibility of ACLF-HBV in the studied Chinese population. This may be partially explained by the relatively higher amount of mature miR-146a and the lower serum level of TNF-α in this genotype group.

Measuring molecular biomarkers in epidemiologic studies: laboratory techniques and biospecimen considerations

The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease-specific molecular biomarkers. High-throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population-based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling.

Smart pooling of mRNA samples for efficient transcript profiling

Gene expression profiling studies are commonly used to study signaling pathways and their impact on transcriptional regulation in plants. In some cases, a profiling study results in expression profiles in which most genes exhibit a small number of differentially expressed states among a large number of samples. In such instances, a pooling approach would help improve the efficiency of the profiling effort by employing fewer microarray chips and ensuring more robust measurement of transcript levels. Smart pooling involves pooling of mRNA samples in an information-efficient manner such that each sample is tested multiple times but always in pools with other samples. The resulting pooled measurements are then decoded to recover the expression profile of all samples in the study. In this protocol, we describe in detail the process of designing smart pooling experiments and decoding their results, which have been used for studying signaling in Arabidopsis root development. Heuristics are provided to select the design parameters that would ensure successful execution of smart pooling.