Quantitative monitoring of gene expression patterns with a complementary DNA microarray

Brain Environment Interactions: Stress, Posttraumatic Stress Disorder, and the Need for a Postmortem Brain Collection

Stress, especially the extreme stress of traumatic events, can alter both neurobiology and behavior. Such extreme environmental situations provide a useful model for understanding environmental influences on human biology and behavior. This paper will review some of the evidence of brain alterations that occur with exposure to environmental stress. This will include recent studies using neuroimaging and will address the need for histological confirmation of imaging study results. We will review the current scientific approaches to understanding brain environment interactions, and then make the case for the collection and study of postmortem brain tissue for the advancement of our understanding of the effects of environment on the brain.Creating a brain tissue collection specifically for the investigation of the effects of extreme environmental stressors fills a gap in the current research; it will provide another of the important pieces to the puzzle that constitutes the scientific investigation of negative effects of environmental exposures. Such a resource will facilitate new discoveries related to the psychiatric illnesses of acute stress disorder and posttraumatic stress disorder, and can enable scientists to correlate structural and functional imaging findings with tissue abnormalities, which is essential to validate the results of recent imaging studies.

Toward a granular molecular-anatomic map of the blood vasculature - single-cell RNA sequencing makes the leap

Single-cell RNA sequencing (scRNAseq) marks the birth of a new era in physiology and medicine. Within foreseeable future, we will know exactly what genes are expressed - and at what levels - in all the different cell types and subtypes that make up our bodies. We will also learn how a particular cell state, whether it occurs during development, tissue repair, or disease, reflects precise changes in gene expression. While profoundly impacting all areas of life science, scRNAseq may lead to a particular leap in vascular biology research. Blood vessels pervade and fulfill essential functions in all organs, but the functions differ. Innumerable organ-specific vascular adaptations and specializations are required. These, in turn, are dictated by differential gene expression by the two principal cellular building blocks of blood vessels: endothelial cells and mural cells. An organotypic vasculature is essential for functions as diverse as thinking, gas exchange, urine excretion, and xenobiotic detoxification in the brain, lung, kidney, and liver, respectively. In addition to the organotypicity, vascular cells also differ along the vascular arterio-venous axis, referred to as zonation, differences that are essential for the regulation of blood pressure and flow. Moreover, gene expression-based molecular changes dictate states of cellular activity, necessary for angiogenesis, vascular permeability, and immune cell trafficking, i.e. functions necessary for development, inflammation, and repair. These different levels of cellular heterogeneity create a nearly infinite phenotypic diversity among vascular cells. In this review, I summarize and exemplify what scRNAseq has brought to the picture in just a few years and point out where it will take us.

A Two-Stage Method Based on Multiobjective Differential Evolution for Gene Selection

Microarray gene expression data provide a prospective way to diagnose disease and classify cancer. However, in bioinformatics, the gene selection problem, i.e., how to select the most informative genes from thousands of genes, remains challenging. This problem is a specific feature selection problem with high-dimensional features and small sample sizes. In this paper, a two-stage method combining a filter feature selection method and a wrapper feature selection method is proposed to solve the gene selection problem. In contrast to common methods, the proposed method models the gene selection problem as a multiobjective optimization problem. Both stages employ the same multiobjective differential evolution (MODE) as the search strategy but incorporate different objective functions. The three objective functions of the filter method are mainly based on mutual information. The two objective functions of the wrapper method are the number of selected features and the classification error of a naive Bayes (NB) classifier. Finally, the performance of the proposed method is tested and analyzed on six benchmark gene expression datasets. The experimental results verified that this paper provides a novel and effective way to solve the gene selection problem by applying a multiobjective optimization algorithm.

Combination of ultrashort PCR and Pyrococcus furiosus Argonaute for DNA detection

A simple and user-friendly nucleic acid sensing platform with 10 aM sensitivity, named USPCRP (combines ultrashort PCR with Pyrococcus furiosus Argonaute cleavage for nuleic acids detection) is reported. The product of this ultrashort PCR could be directly used as a DNA guide to mediate PfAgo cleavage of molecular beacons.

Transcriptomic studies of solventogenic clostridia, Clostridium acetobutylicum and Clostridium beijerinckii

Solventogenic clostridia are not a strictly defined group within the genus Clostridium but its representatives share some common features, i.e. they are anaerobic, non-pathogenic, non-toxinogenic and endospore forming bacteria. Their main metabolite is typically 1-butanol but depending on species and culture conditions, they can form other metabolites such as acetone, isopropanol, ethanol, butyric, lactic and acetic acids, and hydrogen. Although these organisms were previously used for the industrial production of solvents, they later fell into disuse, being replaced by more efficient chemical production. A return to a more biological production of solvents therefore requires a thorough understanding of clostridial metabolism. Transcriptome analysis, which reflects the involvement of individual genes in all cellular processes within a population, at any given (sampling) moment, is a valuable tool for gaining a deeper insight into clostridial life. In this review, we describe techniques to study transcription, summarize the evolution of these techniques and compare methods for data processing and visualization of solventogenic clostridia, particularly the species Clostridium acetobutylicum and Clostridium beijerinckii. Individual approaches for evaluating transcriptomic data are compared and their contributions to advancements in the field are assessed. Moreover, utilization of transcriptomic data for reconstruction of computational clostridial metabolic models is considered and particular models are described. Transcriptional changes in glucose transport, central carbon metabolism, the sporulation cycle, butanol and butyrate stress responses, the influence of lignocellulose-derived inhibitors on growth and solvent production, and other respective topics, are addressed and common trends are highlighted.

Three-dimensional protein microarrays fabricated on reactive microsphere modified COC substrates

Fabrication of three-dimensional (3D) surface structures for the high density immobilization of biomolecules is an effective way to prepare highly sensitive biochips. In this work, a strategy to attach polymeric microspheres on a cyclic olefin copolymer (COC) substrate for the preparation of a 3D protein chip was developed. The COC surface was firstly functionalized by the photograft technique with epoxy groups, which were subsequently converted to amine groups. Then monodisperse poly(styrene-alt-maleic anhydride) (PSM) copolymer microspheres were prepared by self-stabilized precipitation polymerization and deposited as a single layer on a modified COC surface to form a 3D surface texture. The surface roughness of the COC support undergoes a significant increase from 1.4 nm to 37.1 nm after deposition of PSM microspheres with a size of 460 nm, and the modified COC still maintains a transmittance of more than 63% at the fluorescence excitation wavelengths (555 nm and 647 nm). The immobilization efficiency of immunoglobulin G (IgG) on the 3D surface reached 75.6% and the immobilization density was calculated to be 0.255 μg cm^-2, at a probe protein concentration of 200 μg mL^-1. The 3D protein microarray can be rapidly blocked by gaseous ethylenediamine within 10 minutes due to the high reactivity of anhydride groups in PSM microspheres. Immunoassay results show that the 3D protein microarray achieved specific identification of the target protein with a linear detection range from 6.25 ng mL^-1 to 250 ng mL^-1 (R² > 0.99) and a limit of detection of 8.87 ng mL^-1. This strategy offers a novel way to develop high performance polymer-based 3D protein chips.

Correlations of mRNA Levels among Efflux Transporters, Transcriptional Regulators, and Scaffold Proteins in Non-Small-Cell Lung Cancer

Multidrug resistance (MDR) due to enhanced drug efflux activity of tumor cells can severely impact the efficacy of antitumor therapies. We recently showed that increased activity of the efflux transporter P-glycoprotein (P-gp) associated with activation of Snail transcriptional regulators may be mediated mainly by moesin in lung cancer cells. Here, we aimed to systematically evaluate the relationships among mRNA expression levels of efflux transporters (P-gp, breast cancer resistance protein (BCRP), and multidrug resistance-associated protein 2 (MRP2)), scaffold proteins (ezrin (Ezr), radixin (Rdx), and moesin (Msn); ERM proteins), and SNAI family members (Snail, Slug, and Smac) in clinical lung cancer and noncancer samples. We found high correlations between relative (cancer/noncancer) mRNA expression levels of Snail and Msn, Msn and P-gp, Slug and MRP2, and Smuc and BCRP. These findings support our previous conclusion that Snail regulates P-gp activity via Msn and further suggest that Slug and Smuc may contribute to the functional regulation of MRP2 and BCRP, respectively, in lung cancer cells. This trial is registered with UMIN000023923.

Advances in Lymphoma Molecular Diagnostics

Lymphomas encompass a diverse group of malignant lymphoid neoplasms. Over recent years much scientific effort has been undertaken to identify and understand molecular changes in lymphomas, resulting in a wide range of genetic alterations that have been reported across all types of lymphomas. As many of these changes are now incorporated into the World Health Organization’s defined criteria for the diagnostic evaluation of patients with lymphoid neoplasms, their accurate identification is crucial. Even if many alterations are not routinely evaluated in daily clinical practice, they may still have implications in risk stratification, treatment, prognosis or disease monitoring. Moreover, some alterations can be used for targeted treatment. Therefore, these advances in lymphoma molecular diagnostics in some cases have led to changes in treatment algorithms. Here, we give an overview of and discuss advances in molecular techniques in current clinical practice, as well as highlight some of them in a clinical context.

Development and application of a visual microarray for synchronously detecting H5N1, H7N9 and H9N2 avian influenza virus RNA

The aim of this study was to develop a microarray assay for the simultaneous detection of the H5, H7, H9, N1, N9 and N2 genes of the avian influenza virus (AIV) using a Nanogold-streptavidin and silver-stain-enhanced nucleic acid dot-blot hybridisation system. The conserved sequences of H5 genes from H5N1, H7 genes from H7N9, H9 genes from H9N2, N9 genes from H7N9 and N2 genes from H9N2 AIV were cloned, together with that of N1 obtained commercially, and were used as templates for generating the probes using biotin-labeled primers, which targeted the conserved regions of H5, H7, H9, N1, N9 and N2 genes, respectively. The oligonucleotide probes were diluted using the spotting buffer and ddH₂O, and each probe was then spotted to each specific position on the microarray. The PCR products including biotin-labeled lambda, NP, H5, H7, H9, N1, N9 and N2 were mixed, 200 μL of which was then added to the microarray chamber after denaturing. Following a hybridization incubation at 45℃ for 120 min, the microarray was then incubated with nanogold-streptavidin about 4 μg/mL for 30 min. After the supplementary of 200 μL of silver buffer A and silver buffer B in the chamber, the hybridization results were assessed by direct visualization in the dark at room temperature. The microarray assay was optimized and its specificity, sensitivity and stability were evaluated. The optimal conditions comprised a probe concentration of 50 μmol/L, a hybridization temperature of 45℃ and a hybridization time of 2 h. The optimal concentration of nanogold-streptavidin was 4 μg/mL and the optimal staining time was 7 min. The results of specificity evaluation showed that no cross-binding of the probes with each other and no cross-hybridization with Newcastle disease virus, infectious bronchitis virus and infectious laryngotracheitis virus was observed. The optimized microarray assay was significantly more sensitivity than the reverse-transcription PCR assay. The microarray was available after storing at less 90 d at 4 ℃. The optimized microarray assay was validated on clinical specimens and the results showed that it had over 95.6% correlation with reverse-transcription PCR method. Therefore, the microarray assay could be used for the high throughput detection of AIV infections due to H5N1, H7N9 and H9N2.

Concepts and Application of DNA Origami and DNA Self-Assembly: A Systematic Review

With the arrival of the post-Moore Era, the development of traditional silicon-based computers has reached the limit, and it is urgent to develop new computing technology to meet the needs of science and life. DNA computing has become an essential branch and research hotspot of new computer technology because of its powerful parallel computing capability and excellent data storage capability. Due to good biocompatibility and programmability properties, DNA molecules have been widely used to construct novel self-assembled structures. In this review, DNA origami is briefly introduced firstly. Then, the applications of DNA self-assembly in material physics, biogenetics, medicine, and other fields are described in detail, which will aid the development of DNA computational model in the future.

Recent advances in the exonuclease III-assisted target signal amplification strategy for nucleic acid detection

The detection of nucleic acids has become significantly important in molecular diagnostics, gene therapy, mutation analysis, forensic investigations and biomedical development, and so on. In recent years, exonuclease III (Exo III) as an enzyme in the 3'-5' exonuclease family has evolved as a frequently used technique for signal amplification of low level DNA target detection. Different from the traditional target amplification strategies, the Exo III-assisted amplification strategy has been used for target DNA detection through directly amplifying the amounts of signal reagents. The Exo III-assisted amplification strategy has its unique advantages and characters, because the character of non-specific recognition of Exo III can overcome the limitation of a target-to-probe ratio of 1 : 1 in the traditional nucleic acid hybridization assay and acquire higher sensitivity. In this review, we selectively discuss the recent advances in the Exo III-assisted amplification strategy, including the amplification strategy integrated with nanomaterials, biosensors, hairpin probes and other nucleic acid detection methods. We also discuss the strengths and limitations of each strategy and methods to overcome the limitations.

Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle

Metabolomics has been applied to measure the dynamic metabolic responses, to understand the systematic biological networks, to reveal the potential genetic architecture, etc., for human diseases and livestock traits. For example, the current published results include the detected relevant candidate metabolites, identified metabolic pathways, potential systematic networks, etc., for different cattle traits that can be applied for further metabolomic and integrated omics studies. Therefore, summarizing the applications of metabolomics for economic traits is required in cattle. We here provide a comprehensive review about metabolomic analysis and its integration with other omics in five aspects: (1) characterization of the metabolomic profile of cattle; (2) metabolomic applications in cattle; (3) integrated metabolomic analysis with other omics; (4) methods and tools in metabolomic analysis; and (5) further potentialities. The review aims to investigate the existing metabolomic studies by highlighting the results in cattle, integrated with other omics studies, to understand the metabolic mechanisms underlying the economic traits and to provide useful information for further research and practical breeding programs in cattle.

Identifying disease-gene associations using a convolutional neural network-based model by embedding a biological knowledge graph with entity descriptions

Understanding the role of genes in human disease is of high importance. However, identifying genes associated with human diseases requires laborious experiments that involve considerable effort and time. Therefore, a computational approach to predict candidate genes related to complex diseases including cancer has been extensively studied. In this study, we propose a convolutional neural network-based knowledge graph-embedding model (KGED), which is based on a biological knowledge graph with entity descriptions to infer relationships between biological entities. As an application demonstration, we generated gene-interaction networks for each cancer type using gene-gene relationships inferred by KGED. We then analyzed the constructed gene networks using network centrality measures, including betweenness, closeness, degree, and eigenvector centrality metrics, to rank the central genes of the network and identify highly correlated cancer genes. Furthermore, we evaluated our proposed approach for prostate, breast, and lung cancers by comparing the performance with that of existing approaches. The KGED model showed improved performance in predicting cancer-related genes using the inferred gene-gene interactions. Thus, we conclude that gene-gene interactions inferred by KGED can be helpful for future research, such as that aimed at future research on pathogenic mechanisms of human diseases, and contribute to the field of disease treatment discovery.

AI applications in functional genomics

We review the current applications of artificial intelligence (AI) in functional genomics. The recent explosion of AI follows the remarkable achievements made possible by "deep learning", along with a burst of "big data" that can meet its hunger. Biology is about to overthrow astronomy as the paradigmatic representative of big data producer. This has been made possible by huge advancements in the field of high throughput technologies, applied to determine how the individual components of a biological system work together to accomplish different processes. The disciplines contributing to this bulk of data are collectively known as functional genomics. They consist in studies of: i) the information contained in the DNA (genomics); ii) the modifications that DNA can reversibly undergo (epigenomics); iii) the RNA transcripts originated by a genome (transcriptomics); iv) the ensemble of chemical modifications decorating different types of RNA transcripts (epitranscriptomics); v) the products of protein-coding transcripts (proteomics); and vi) the small molecules produced from cell metabolism (metabolomics) present in an organism or system at a given time, in physiological or pathological conditions. After reviewing main applications of AI in functional genomics, we discuss important accompanying issues, including ethical, legal and economic issues and the importance of explainability.

Prospective clinical trial testing COXEN-based gene expression models of chemosensitivity in dogs with spontaneous osteosarcoma

BACKGROUND

This study is a prospective clinical trial in dogs with osteosarcoma testing a gene expression model (GEM) predicting the chemosensitivity of tumors to carboplatin (CARBO) or doxorubicin (DOX) developed using the COXEN method.

PATIENTS AND METHODS

Sixty dogs with appendicular osteosarcoma were enrolled in this trial. RNA isolation and gene expression profiling were conducted with 2 biopsies for 54/63 screened tumors, and with a single biopsy for 9 tumors. Resulting gene expression data were used for calculation of a COXEN score for CARBO and DOX based on a previous study showing the significance of this predictor on patient outcome utilizing retrospective data (BMC Bioinformatics 17:93). Dogs were assigned adjuvant CARBO, DOX or the combination based on the results of the COXEN score following surgical removal of the tumor via amputation and were monitored for disease progression by chest radiograph every 2 months.

RESULTS

The COXEN predictor of chemosensitivity to CARBO or DOX was not a significant predictor of progression-free interval or overall survival for the trial participants. The calculation of DOX COXEN score using gene expression data from two independent biopsies of the same tumor were highly correlated (P < 0.0001), whereas the calculated CARBO COXEN score was not (P = 0.3039).

CONCLUSION

The COXEN predictor of chemosensitivity to CARBO or DOX is not a significant predictor of outcome when utilized in this prospective study. This trial represents the first prospective trial of a GEM predictor of chemosensitivity and establishes pet dogs with cancer as viable surrogates for prospective trials of prognostic indicators.

An Optical Smartphone-Based Inspection Platform for Identification of Diseased Orchids

Infections of orchids by the Odontoglossum ringspot virus or Cymbidium mosaic virus cause orchid disfiguration and are a substantial source of economic loss for orchid farms. Although immunoassays can identify these infections, immunoassays are expensive, time consuming, and labor consuming and limited to sampling-based testing methods. This study proposes a noncontact inspection platform that uses a spectrometer and Android smartphone. When orchid leaves are illuminated with a handheld optical probe, the Android app based on the Internet of Things and artificial intelligence can display the measured florescence spectrum and determine the infection status within 3 s by using an algorithm hosted on a remote server. The algorithm was trained on optical data and the results of polymerase chain reaction assays. The testing accuracy of the algorithm was 89%. The area under the receiver operating characteristic curve was 91%; thus, the platform with the algorithm was accurate and convenient for infection screening in orchids.

RiboRid: A low cost, advanced, and ultra-efficient method to remove ribosomal RNA for bacterial transcriptomics

RNA sequencing techniques have enabled the systematic elucidation of gene expression (RNA-Seq), transcription start sites (differential RNA-Seq), transcript 3′ ends (Term-Seq), and post-transcriptional processes (ribosome profiling). The main challenge of transcriptomic studies is to remove ribosomal RNAs (rRNAs), which comprise more than 90% of the total RNA in a cell. Here, we report a low-cost and robust bacterial rRNA depletion method, RiboRid, based on the enzymatic degradation of rRNA by thermostable RNase H. This method implemented experimental considerations to minimize nonspecific degradation of mRNA and is capable of depleting pre-rRNAs that often comprise a large portion of RNA, even after rRNA depletion. We demonstrated the highly efficient removal of rRNA up to a removal efficiency of 99.99% for various transcriptome studies, including RNA-Seq, Term-Seq, and ribosome profiling, with a cost of approximately $10 per sample. This method is expected to be a robust method for large-scale high-throughput bacterial transcriptomic studies.

Removal of ribosomal RNAs, a major constituent (over 90%) of cellular RNA is a critical experimental step for transcriptomic studies that deal with messenger RNAs. In this manuscript, we describe a robust method to subtract ribosomal RNA from various RNA samples. The method is based on the enzymatic degradation of target RNA by short complementary DNA and RNA:DNA duplex specific nuclease. The method comprises carefully designed experimental procedures to minimize experimental bias and unwanted removal of messenger RNAs. We validate the method on various types of transcriptomic studies for seven diverse bacterial species. This method successfully removed ribosomal RNA with over 99% of efficiency and it was comparable to commercial systems even for degraded RNA samples at a fraction of a cost.

High-resolution imaging and fast number estimation of suspended particles using dewetted polymer microlenses in a microfluidic channel

We have fabricated polymer micro-lens array by self-organized dewetting inside the microchannel, which shows remarkable enhancement in the resolution, contrast and more than 10 times add-on magnification to a microscope. These lenses are demonstrated to resolve sub-micrometer features and detect moving micro-particles when suspension is flown in a microchannel. Polystyrene (PS) micro-lenses are fabricated on a polydimethylsiloxane (PDMS) substrate using the controlled dewetting of PS thin film then this PDMS substrate is used to close the microchannel with inverted micro-lenses on it. An aqueous suspension of polystyrene particles is flown through the microchannel and we have observed the particles through an optical microscope. Focusing and magnification through PS micro-lenses is analyzed to get a quantitative estimate of the particle number density in the solution. This method offers a promising low-cost high throughput solution for determining the approximate number density of flowing particles or suitably stained biological cells. Particularly in a pathology lab it can tremendously increase detection limit by enabling visibility of sub-micrometer pathogens using a standard laboratory microscope.

Advancement in Salmonella Detection Methods: From Conventional to Electrochemical-Based Sensing Detection

Large-scale food-borne outbreaks caused by Salmonella are rarely seen nowadays, thanks to the advanced nature of the medical system. However, small, localised outbreaks in certain regions still exist and could possess a huge threat to the public health if eradication measure is not initiated. This review discusses the progress of Salmonella detection approaches covering their basic principles, characteristics, applications, and performances. Conventional Salmonella detection is usually performed using a culture-based method, which is time-consuming, labour intensive, and unsuitable for on-site testing and high-throughput analysis. To date, there are many detection methods with a unique detection system available for Salmonella detection utilising immunological-based techniques, molecular-based techniques, mass spectrometry, spectroscopy, optical phenotyping, and biosensor methods. The electrochemical biosensor has growing interest in Salmonella detection mainly due to its excellent sensitivity, rapidity, and portability. The use of a highly specific bioreceptor, such as aptamers, and the application of nanomaterials are contributing factors to these excellent characteristics. Furthermore, insight on the types of biorecognition elements, the principles of electrochemical transduction elements, and the miniaturisation potential of electrochemical biosensors are discussed.

Genome sequencing guide: An introductory toolbox to whole-genome analysis methods

To fully appreciate genetics, one must understand the link between genotype (DNA sequence) and phenotype (observable characteristics). Advances in high-throughput genomic sequencing technologies and applications, so-called "-omics," have made genetic sequencing readily available across fields in biology from applications in non-traditional study organisms to precision medicine. Thus, understanding these tools is critical for any biologist, especially those early in their career. This comprehensive review discusses the chronological development of different sequencing methods, the bioinformatics steps to analyzing this data, and social and ethical issues raised by these techniques that must be discussed and evaluated, including anticipatory guides and discussion questions for active engagement in the classroom. Additionally, the Supporting Information includes a case study to apply technical and ethical concepts from the text.

Controlling Surface Wettability for Automated In Situ Array Synthesis and Direct Bioscreening

The in situ synthesis of biomolecules on glass surfaces for direct bioscreening can be a powerful tool in the fields of pharmaceutical sciences, biomaterials, and chemical biology. However, it is still challenging to 1) achieve this conventional multistep combinatorial synthesis on glass surfaces with small feature sizes and high yields and 2) develop a surface which is compatible with solid-phase syntheses, as well as the subsequent bioscreening. This work reports an amphiphilic coating of a glass surface on which small droplets of polar aprotic organic solvents can be deposited with an enhanced contact angle and inhibited motion to permit fully automated multiple rounds of the combinatorial synthesis of small-molecule compounds and peptides. This amphiphilic coating can be switched into a hydrophilic network for protein- and cell-based screening. Employing this in situ synthesis method, chemical space can be probed via array technology with unprecedented speed for various applications, such as lead discovery/optimization in medicinal chemistry and biomaterial development.

Arabidopsis Coexpression Tool: a tool for gene coexpression analysis in Arabidopsis thaliana

Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana, identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.

Macrodrop-Impact-Mediated Fluid Microdispensing

High-resolution fluid dispensing techniques play a critical role in modern digital microfluidics, micro-biosensing, and advanced fabrication. Though most of existing dispensers can achieve precise and high-throughput fluid dispensing, they suffer from some inherent problems, such as specially fabricated dispensing micronozzles/microtips, large operating systems, low volume tunability, and poor performance for low surface tension liquids and liquids containing solid/liquid additives. Herein, the authors propose a facile, low-frequency micro dispensing technique based on the Rayleigh-Plateau instability of singular liquid jets, which are stimulated by the air cavity collapse arising in the impact of microliter drops on non-wetting surfaces. This novel dispensing strategy is capable to produce single microdrops of low-viscosity liquids with a tunable volume from picoliters to nanoliters, and the operational surface tension range covers most laboratory solvents. The dispensing function is implemented without using small-dimension nozzles/tips and enables handling diverse complex liquids. Moreover, the rather simple operating platform allows the integration of the whole dispensing function into a handy portable device with a low cost. Employing this microdispensing technique, the authors have controlled microchemical reactions, handled liquid samples in biological analysis, and fabricated smart materials and devices. The authors envision that this rational microdrop generator would find applications in various research areas.

Computational Phosphorylation Network Reconstruction: An Update on Methods and Resources

Most proteins undergo some form of modification after translation, and phosphorylation is one of the most relevant and ubiquitous post-translational modifications. The succession of protein phosphorylation and dephosphorylation catalyzed by protein kinase and phosphatase, respectively, constitutes a key mechanism of molecular information flow in cellular systems. The protein interactions of kinases, phosphatases, and their regulatory subunits and substrates are the main part of phosphorylation networks. To elucidate the landscape of phosphorylation events has been a central goal pursued by both experimental and computational approaches. Substrate specificity (e.g., sequence, structure) or the phosphoproteome has been utilized in an array of different statistical learning methods to infer phosphorylation networks. In this chapter, different computational phosphorylation network inference-related methods and resources are summarized and discussed.

OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security

The incredible success of crop breeding and agricultural innovation in the last century greatly contributed to the Green Revolution, which significantly increased yields and ensures food security, despite the population explosion. However, new challenges such as rapid climate change, deteriorating soil, and the accumulation of pollutants require much faster responses and more effective solutions that cannot be achieved through traditional breeding. Further prospects for increasing the efficiency of agriculture are undoubtedly associated with the inclusion in the breeding strategy of new knowledge obtained using high-throughput technologies and new tools in the future to ensure the design of new plant genomes and predict the desired phenotype. This article provides an overview of the current state of research in these areas, as well as the study of soil and plant microbiomes, and the prospective use of their potential in a new field of microbiome engineering. In terms of genomic and phenomic predictions, we also propose an integrated approach that combines high-density genotyping and high-throughput phenotyping techniques, which can improve the prediction accuracy of quantitative traits in crop species.

Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.

MP3RNA-seq: Massively parallel 3' end RNA sequencing for high-throughput gene expression profiling and genotyping

Transcriptome deep sequencing (RNA-seq) has become a routine method for global gene expression profiling. However, its application to large-scale experiments remains limited by cost and labor constraints. Here we describe a massively parallel 3' end RNA-seq (MP3RNA-seq) method that introduces unique sample barcodes during reverse transcription to permit sample pooling immediately following this initial step. MP3RNA-seq allows for handling of hundreds of samples in a single experiment, at a cost of about $6 per sample for library construction and sequencing. MP3RNA-seq is effective for not only high-throughput gene expression profiling, but also genotyping. To demonstrate its utility, we applied MP3RNA-seq to 477 double haploid lines of maize. We identified 19,429 genes expressed in at least 50% of the lines and 35,836 high-quality single nucleotide polymorphisms for genotyping analysis. Armed with these data, we performed expression and agronomic trait quantitative trait locus (QTL) mapping and identified 25,797 expression QTLs for 15,335 genes and 21 QTLs for plant height, ear height, and relative ear height. We conclude that MP3RNA-seq is highly reproducible, accurate, and sensitive for high-throughput gene expression profiling and genotyping, and should be generally applicable to most eukaryotic species.

Clip Chemistry: Diverse (Bio)(macro)molecular and Material Function through Breaking Covalent Bonds

In the two decades since the introduction of the "click chemistry" concept, the toolbox of "click reactions" has continually expanded, enabling chemists, materials scientists, and biologists to rapidly and selectively build complexity for their applications of interest. Similarly, selective and efficient covalent bond breaking reactions have provided and will continue to provide transformative advances. Here, we review key examples and applications of efficient, selective covalent bond cleavage reactions, which we refer to herein as "clip reactions." The strategic application of clip reactions offers opportunities to tailor the compositions and structures of complex (bio)(macro)molecular systems with exquisite control. Working in concert, click chemistry and clip chemistry offer scientists and engineers powerful methods to address next-generation challenges across the chemical sciences.

Controlling the wetting and evaporation dynamics of non-ideal volatile binary solutions

HYPOTHESIS

Volatile binary liquid samples on wetting substrates are known to undergo either spreading or contraction tendencies, as a result of solutal Marangoni stresses due to differential volatility. Enhanced spreading is commonly thought to occur when the lower surface tension component is more 'volatile', while contraction is expected otherwise. We seek to test the limits of this scenario for various configurations such as sessile drops with free or pinned contact lines, without or with microparticles, and tears-of-wine menisci.

EXPERIMENTS

We consider isopropanol- and ethanol-water mixtures, important in numerous applications. We conduct interferometric experiments with sessile droplets for multiple combinations of the initial concentration and controlled ambient humidity (water vapour only), essentially covering the entire range of these parameters. Experiments are also carried out for other configurations mentioned above.

FINDINGS

Contraction regimes are found in certain situations where spreading is expected, despite the alcohols being more volatile than water. Furthermore, regime reversals occur between cases with different initial liquid concentrations even at zero humidity, and are not necessarily associated with the existence of an azeotropic composition. Such surprising observations are rationalized by a simple model highlighting the often overlooked role of the diffusion coefficient ratio of the two vapours in conjunction with the non-ideality of the mixture. Our picture of the phenomenon is demonstrated to be universal for all configurations studied.

Therapeutic mesenchymal stromal stem cells: Isolation, characterization and role in equine regenerative medicine and metabolic disorders

Mesenchymal stromal cells (MSC) have become a popular treatment modality in equine orthopaedics. Regenerative therapies are especially interesting for pathologies like complicated tendinopathies of the distal limb, osteoarthritis, osteochondritis dissecans (OCD) and more recently metabolic disorders. Main sources for MSC harvesting in the horse are bone marrow, adipose tissue and umbilical cord blood. While the acquisition of umbilical cord blood is fairly easy and non-invasive, extraction of bone marrow and adipose tissue requires more invasive techniques. Characterization of the stem cells as a result of any isolation method, is also a crucial step for the confirmation of the cells' stemness properties; thus, three main characteristics must be fulfilled by these cells, namely: adherence, expression of a series of well-defined differentiation clusters as well as pluripotency. EVs, resulting from the paracrine action of MSCs, also play a key role in the therapeutic mechanisms mediated by stem cells; MSC-EVs are thus largely implicated in the regulation of proliferation, maturation, polarization and migration of various target cells. Evidence that EVs alone represent a complex network 0involving different soluble factors and could then reflect biophysical characteristics of parent cells has fuelled the importance of developing highly specific techniques for their isolation and analysis. All these aspects related to the functional and technical understanding of MSCs will be discussed and summarized in this review.

Integration of Transformative Platforms for the Discovery of Causative Genes in Cardiovascular Diseases

Cardiovascular diseases are the leading cause of morbidity and mortality worldwide. Genome-wide association studies (GWAS) are powerful epidemiological tools to find genes and variants associated with cardiovascular diseases while follow-up biological studies allow to better understand the etiology and mechanisms of disease and assign causality. Improved methodologies and reduced costs have allowed wider use of bulk and single-cell RNA sequencing, human-induced pluripotent stem cells, organoids, metabolomics, epigenomics, and novel animal models in conjunction with GWAS. In this review, we feature recent advancements relevant to cardiovascular diseases arising from the integration of genetic findings with multiple enabling technologies within multidisciplinary teams to highlight the solidifying transformative potential of this approach. Well-designed workflows integrating different platforms are greatly improving and accelerating the unraveling and understanding of complex disease processes while promoting an effective way to find better drug targets, improve drug design and repurposing, and provide insight towards a more personalized clinical practice.

Anno genominis XX: 20 years of Arabidopsis genomics

Twenty years ago, the Arabidopsis thaliana genome sequence was published. This was an important moment as it was the first sequenced plant genome and explicitly brought plant science into the genomics era. At the time, this was not only an outstanding technological achievement, but it was characterized by a superb global collaboration. The Arabidopsis genome was the seed for plant genomic research. Here, we review the development of numerous resources based on the genome that have enabled discoveries across plant species, which has enhanced our understanding of how plants function and interact with their environments.

Structure and Oligonucleotide Binding Efficiency of Differently Prepared Click Chemistry-Type DNA Microarray Slides Based on 3-Azidopropyltrimethoxysilane

The structural characterization of glass slides surface-modified with 3-azidopropyltrimethoxysilane and used for anchoring nucleic acids, resulting in the so-called DNA microarrays, is presented. Depending on the silanization conditions, the slides were found to show different oligonucleotide binding efficiency, thus, an attempt was made to correlate this efficiency with the structural characteristics of the silane layers. Atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and X-ray reflectometry (XRR) measurements provided information on the surface topography, chemical composition and thickness of the silane films, respectively. The surface for which the best oligonucleotides binding efficiency is observed, has been found to consist of a densely-packed silane layer, decorated with a high-number of additional clusters that are believed to host exposed azide groups.

Machine learning-integrated omics for the risk and safety assessment of nanomaterials

With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessities to advanced electronics, health care products and medicines. Therefore, nanoproducts, however, can have negative side effects and must be strictly monitored to avoid negative outcomes. Future toxicity and safety challenges regarding nanomaterial incorporation into consumer products, including rapid addition of nanomaterials with diverse functionalities and attributes, highlight the limitations of traditional safety evaluation tools. Currently, artificial intelligence and machine learning algorithms are envisioned for enhancing and improving the nano-bio-interaction simulation and modeling, and they extend to the post-marketing surveillance of nanomaterials in the real world. Thus, hyphenation of machine learning with biology and nanomaterials could provide exclusive insights into the perturbations of delicate biological functions after integration with nanomaterials. In this review, we discuss the potential of combining integrative omics with machine learning in profiling nanomaterial safety and risk assessment and provide guidance for regulatory authorities as well.

Myeloid Arginase 1 Insufficiency Exacerbates Amyloid-β Associated Neurodegenerative Pathways and Glial Signatures in a Mouse Model of Alzheimer's Disease: A Targeted Transcriptome Analysis

Brain myeloid cells, include infiltrating macrophages and resident microglia, play an essential role in responding to and inducing neurodegenerative diseases, such as Alzheimer's disease (AD). Genome-wide association studies (GWAS) implicate many AD casual and risk genes enriched in brain myeloid cells. Coordinated arginine metabolism through arginase 1 (Arg1) is critical for brain myeloid cells to perform biological functions, whereas dysregulated arginine metabolism disrupts them. Altered arginine metabolism is proposed as a new biomarker pathway for AD. We previously reported Arg1 deficiency in myeloid biased cells using lysozyme M (LysM) promoter-driven deletion worsened amyloidosis-related neuropathology and behavioral impairment. However, it remains unclear how Arg1 deficiency in these cells impacts the whole brain to promote amyloidosis. Herein, we aim to determine how Arg1 deficiency driven by LysM restriction during amyloidosis affects fundamental neurodegenerative pathways at the transcriptome level. By applying several bioinformatic tools and analyses, we found that amyloid-β (Aβ) stimulated transcriptomic signatures in autophagy-related pathways and myeloid cells' inflammatory response. At the same time, myeloid Arg1 deficiency during amyloidosis promoted gene signatures of lipid metabolism, myelination, and migration of myeloid cells. Focusing on Aβ associated glial transcriptomic signatures, we found myeloid Arg1 deficiency up-regulated glial gene transcripts that positively correlated with Aβ plaque burden. We also observed that Aβ preferentially activated disease-associated microglial signatures to increase phagocytic response, whereas myeloid Arg1 deficiency selectively promoted homeostatic microglial signature that is non-phagocytic. These transcriptomic findings suggest a critical role for proper Arg1 function during normal and pathological challenges associated with amyloidosis. Furthermore, understanding pathways that govern Arg1 metabolism may provide new therapeutic opportunities to rebalance immune function and improve microglia/macrophage fitness.

Non-Covalent Microarrays from Synthetic Amino-Terminating Glycans-Implications in Expanding Glycan Microarray Diversity and Platform Comparison

Glycan microarrays have played important roles in detection and specificity assignment of glycan-recognition by proteins. However, the size and diversity of glycan libraries in current microarray systems are small compared to estimated glycomes, and these may lead to missed detection or incomplete assignment. For microarray construction, covalent and non-covalent immobilization are the two types of methods used, but a direct comparison of results from the two platforms is required. Here we develop a chemical strategy to prepare lipid-linked probes from both naturally-derived aldehyde-terminating and synthetic amino-terminating glycans that addresses the two aspects: expansion of sequence-defined glycan libraries and comparison of the two platforms. We demonstrate the specific recognition by plant and mammalian lectins, carbohydrate-binding modules and antibodies, and the overall similarities from the two platforms. Our results provide new knowledge on unique glycan-binding specificities for the immune-receptor Dectin-1 towards β-glucans and the interaction of rotavirus P[19] adhesive protein with mucin O-glycan cores.

A novel ratiometric electrochemical biosensing strategy based on T7 exonuclease-assisted homogenous target recycling coupling hairpin assembly-triggered double-signal output for the multiple amplified detection of miRNA

A novel ratiometric electrochemical biosensing strategy based on T7 exonuclease (T7 Exo)-assisted homogenous target recycling coupling hairpin assembly triggered dual-signal output was proposed for the accurate and sensitive detection of microRNA-141 (miRNA-141). Concretely, in the presence of target miRNA, abundant signal transduction probes were released via the T7 Exo-assisted homogenous target recycling amplification, which could be captured by the specially designed ferrocene-labeled hairpin probe (Fc-H1) on -electrode interface and triggered the nonenzymatic catalytic hairpin assembly (Fc-H1 + MB-H2) to realize the cascade signal amplification and dual-signal output. Through such a conformational change process, the electrochemical signal of Fc (IFc) and MB (IMB) is proportionally and substantially decreased and increased. Therefore, the signal ratio of IMB/IFc can be employed to accurately reflect the true level of original miRNA. Benefiting from the efficient integration of the T7 Exo-assisted target recycle, nonenzymatic hairpin assembly and dual-signal output mode, the proposed sensor could realize the amplified detection of miRNA-141 effectively with a wide detection range from 1 fM to 100 pM, and a detection limit of 200 aM. Furthermore, it exhibits outstanding sequence specificity to discriminate mismatched RNA, acceptable reproducibility and feasibility for real sample. This strategy effectively integrated the advantages of multiple amplification and ratiometric output modes, which could provide an accurate and efficient method in biosensing and clinical diagnosis.

Identification of differentially expressed genes and signaling pathways in human conjunctiva and reproductive tract infected with Chlamydia trachomatis

BACKGROUND

Currently, Chlamydia trachomatis-specific host defense mechanisms in humans remain poorly defined. To study the characteristics of host cells infected early with Chlamydia trachomatis, we used bioinformatics methods to analyze the RNA transcription profiles of the conjunctiva, fallopian tubes, and endometrium in humans infected with Chlamydia trachomatis.

METHOD

The gene expression profiles of GSE20430, GSE20436, GSE26692, and GSE41075 were downloaded from the Gene Expression Synthesis (GEO) database. Then, we obtained the differentially expressed genes (DEGs) through the R 4.0.1 software. STRING was used to construct protein-protein interaction (PPI) networks; then, the Cytoscape 3.7.2 software was used to visualize the PPI and screen hub genes. GraphPad Prism 8.0 software was used to verify the expression of the hub gene. In addition, the gene-miRNA interaction was constructed on the NetworkAnalyst 3.0 platform using the miRTarBase v8.0 database.

RESULTS

A total of 600 and 135 DEGs were screened out in the conjunctival infection group and the reproductive tract infection group, respectively. After constructing a PPI network and verifying the hub genes, CSF2, CD40, and CSF3 in the reproductive tract infection group proved to have considerable statistical significance.

CONCLUSION

In our research, the key genes in the biological process of reproductive tract infection with Chlamydia trachomatis were clarified through bioinformatics analysis. These hub genes may be further used in clinical treatment and clinical diagnosis.

A Compact Detection Platform Based on Gradient Guided-Mode Resonance for Colorimetric and Fluorescence Liquid Assay Detection

This paper presents a compact spectral detection system for common fluorescent and colorimetric assays. This system includes a gradient grating period guided-mode resonance (GGP-GMR) filter and charge-coupled device. In its current form, the GGP-GMR filter, which has a size of less than 2.5 mm, can achieve a spectral detection range of 500-700 nm. Through the direct measurement of the fluorescence emission, the proposed system was demonstrated to detect both the peak wavelength and its corresponding intensity. One fluorescent assay (albumin) and two colorimetric assays (albumin and creatinine) were performed to demonstrate the practical application of the proposed system for quantifying common liquid assays. The results of our system exhibited suitable agreement with those of a commercial spectrometer in terms of the assay sensitivity and limit of detection (LOD). With the proposed system, the fluorescent albumin, colorimetric albumin, and colorimetric creatinine assays achieved LODs of 40.99 and 398 and 25.49 mg/L, respectively. For a wide selection of biomolecules in point-of-care applications, the spectral detection range achieved by the GGP-GMR filter can be further extended and the simple and compact optical path configuration can be integrated with a lab-on-a-chip system.

Design of New Improved Curcumin Derivatives to Multi-targets of Cancer and Inflammation

BACKGROUND

Curcumin is a major active principle of Curcuma longa. There are more than 1700 citations in the Medline, reflecting various biological effects of curcumin. Most of these biological activities are associated with the antioxidant, anti-inflammatory and antitumor activity of the molecule. Several reports suggest various targets of natural curcumin that include growth factors, growth factor receptor, cytokines, enzymes and gene regulators of apoptosis. This review focuses on the improved curcumin derivatives that target the cancer and inflammation.

METHODOLOGY

In this present review, we explored the anticancer drugs with curcumin-based drugs under pre-clinical and clinical studies with critical examination. Based on the strong scientific reports of patentable and non-patented literature survey, we have investigated the mode of the interactions of curcumin-based molecules with the target molecules.

RESULTS

Advanced studies have added new dimensions of the molecular response of cancer cells to curcumin at the genomic level. However, poor bioavailability of the molecule seems to be the major limitation of the curcumin. Several researchers have been involved to improve the curcumin derivatives to overcome this limitation. Sufficient data of clinical trials to various cancers that include multiple myeloma, pancreatic cancer and colon cancer, have also been discussed.

CONCLUSION

The detailed analysis of the structure-activity relationship (SAR) and common synthesis of curcumin-based derivatives have been discussed in the review. Utilising the predictions of in silico coupled with validation reports of in vitro and in vivo studies have concluded many targets for curcumin. Among them, cancer-related inflammation genes regulating curcumin-based molecules are a very promising target to overcome hurdles in the multimodality therapy of cancer.

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.

Soil redox dynamics under dynamic hydrologic regimes - A review

Electron transfer (redox) reactions, mediated by soil microbiota, modulate elemental cycling and, in part, establish the redox poise of soil systems. Understanding soil redox processes significantly improves our ability to characterize coupled biogeochemical cycling in soils and aids in soil health management. Redox-sensitive species exhibit different reactivity, mobility, and toxicity subjected to their redox state. Thus, it is crucial to quantify the redox potential (E_h) in soils and to characterize the dominant redox couples therein. Several, often coupled, external drivers, can influence E_h. Among these factors, soil hydrology dominates. It controls soil physical properties that in turn further regulates E_h. Soil spatial heterogeneity and temporally dynamic hydrologic regimes yield complex distributions of E_h. Soil redox processes have been studied under various environmental conditions, including relatively static and dynamic hydrologic regimes. Our focus here is on dynamic, variably water-saturated environments. Herein, we review previous studies on soil redox dynamics, with a specific focus on dynamic hydrologic regimes, provide recommendations on knowledge gaps, and targeted future research needs and directions. We review (1) the role of soil redox conditions on the soil chemical-species cycling of organic carbon, nitrogen, phosphorus, redox-active metals, and organic contaminants; (2) interactions between microbial activity and redox state in the near-surface and deep subsurface soil, and biomolecular methods to reveal the role of microbes in the redox processes; (3) the effects of dynamic hydrologic regimes on chemical-species cycling and microbial dynamics; (4) the experimental setups for mimicking different hydrologic regimes at both laboratory and field scales. Finally, we identify the current knowledge gaps related to the study of soil redox dynamics under different hydrologic regimes: (1) fluctuating conditions in the deep subsurface; (2) the use of biomolecular tools to understand soil biogeochemical processes beyond nitrogen; (3) limited current field measurements and potential alternative experimental setups.

[New technologies for renal pathology: Transcriptomics on paraffin-embedded fixed tissue]

The development of new high-throughput technologies in genomics and then in transcriptomics has modified clinical approach in nephrology. At the interface between high-throughput technologies (microarray, new generation sequencing «NGS») and few mRNA analysis (reverse transcriptase quantitative PCR [RT-qPCR]), the nCounter® of NanoString® offers a new and complementary approach. Capable of analyzing formalin-fixed paraffin-embedded samples, this technology is a credible candidate for implanting transcriptomics in clinical routine.

Chromosomal analysis for embryos from balanced chromosomal rearrangement carriers using next generation sequencing

We aimed to use next generation sequencing (NGS) to investigate chromosomal abnormalities in blastocyst trophectoderm (TE) samples, and reproductive outcomes with the different types of chromosomal rearrangements (CR) and for each sex of CR carrier. A total of 1189 blastocyst TE samples were evaluated using NGS to detect chromosomal unbalanced translocations as well as aneuploidy, including blastocytes from 637 blastocysts from carriers of balanced CR and 552 blastocysts from carriers of normal chromosomes. The optimal embryos had lower chromosomal abnormality rates compared to the poor-quality embryos. The experimental group had significantly reduced rates of normal embryos and euploidy, and higher rates of total abnormalities, aneuploidy and unbalanced chromosomal aberrations. Carriers of reciprocal translocations had a reduced rate of normal embryos and an increased percentage of embryos with total abnormalities and unbalanced chromosomal aberrations compared with carriers of Robertsonian translocations. Couples with female carriers of chromosomal abnormalities had significantly reduced rates of normal embryos and euploidy, and a higher percentage of embryos with total abnormalities, aneuploidy, and unbalanced chromosomal aberrations compared with couples of male carriers. Our preimplantation genetic testing (PGT) study identified higher rates of chromosomal abnormalities, including chromosomal unbalanced translocations and aneuploidy, in blastocysts from CR carriers, especially from the female carriers, in a Chinese population. The PGT cycles successfully improved clinical outcomes by increasing the fertilization rate and reducing the early spontaneous abortion rate compared with the in vitro fertilization and intracytoplasmic sperm injection cycles, especially for CR carriers.

Omics analyses in keratoconus: from transcriptomics to proteomics

Purpose of Review

To summarize the recent advances in transcriptomics and proteomics studies of keratoconus using advanced genome-wide gene and protein expression profiling techniques.

Recent Findings

Second-generation sequencing including RNA sequencing has been widely used to characterize the genome-wide gene expression in corneal tissues or cells affected by keratoconus. Due to different sample types, sequencing platforms, and analysis pipeline, different lists of genes have been identified to be differentially expressed in KC-affected samples. Gene ontology and pathway/network analyses have indicated the involvement of genes related with extracellular matrix, WNT-signaling, TGFβ pathway, and NRF2-regulated network. High throughput proteomics studies using mass spectrometry have uncovered many KC-related protein molecules in pathways related with cytoskeleton, cell matrix, TGFβ signaling, and extracellular matrix remodeling, consistent with gene expression profiling.

Summary

Both transcriptomics and proteomics studies using genome-wide gene/protein expression profiling techniques have identified significant genes/proteins that may contribute to the pathogenesis of keratoconus. These molecules may be involved in functional categories related with extracellular matrix and TGFβ signaling. It is necessary to perform comprehensive gene/protein expression studies using larger sample size, same type of samples, up-to-date platform and bioinformatics tools.

Microfluidic-based virus detection methods for respiratory diseases

With the recent SARS-CoV-2 outbreak, the importance of rapid and direct detection of respiratory disease viruses has been well recognized. The detection of these viruses with novel technologies is vital in timely prevention and treatment strategies for epidemics and pandemics. Respiratory viruses can be detected from saliva, swab samples, nasal fluid, and blood, and collected samples can be analyzed by various techniques. Conventional methods for virus detection are based on techniques relying on cell culture, antigen-antibody interactions, and nucleic acids. However, these methods require trained personnel as well as expensive equipment. Microfluidic technologies, on the other hand, are one of the most accurate and specific methods to directly detect respiratory tract viruses. During viral infections, the production of detectable amounts of relevant antibodies takes a few days to weeks, hampering the aim of prevention. Alternatively, nucleic acid-based methods can directly detect the virus-specific RNA or DNA region, even before the immune response. There are numerous methods to detect respiratory viruses, but direct detection techniques have higher specificity and sensitivity than other techniques. This review aims to summarize the methods and technologies developed for microfluidic-based direct detection of viruses that cause respiratory infection using different detection techniques. Microfluidics enables the use of minimal sample volumes and thereby leading to a time, cost, and labor effective operation. Microfluidic-based detection technologies provide affordable, portable, rapid, and sensitive analysis of intact virus or virus genetic material, which is very important in pandemic and epidemic events to control outbreaks with an effective diagnosis.

Analyzing the genetic characteristics of a tryptophan-overproducing Escherichia coli

L-tryptophan (L-trp) production in Escherichia coli has been developed by employing random mutagenesis and selection for a long time, but this approach produces an unclear genetic background. Here, we generated the L-trp overproducer TPD5 by combining an intracellular L-trp biosensor and fluorescence-activated cell sorting (FACS) in E. coli, and succeeded in elucidating the genetic basis for L-trp overproduction. The most significant identified positive mutations affected TnaA (deletion), AroG (S211F), TrpE (A63V), and RpoS (nonsense mutation Q33*). The underlying structure-function relationships of the feedback-resistant AroG (S211F) and TrpE (A63V) mutants were uncovered based on protein structure modeling and molecular dynamics simulations, respectively. According to transcriptomic analysis, the global regulator RpoS not only has a great influence on cell growth and morphology, but also on carbon utilization and the direction of carbon flow. Finally, by balancing the concentrations of the L-trp precursors' serine and glutamine based on the above analysis, we further increased the titer of L-trp to 3.18 g/L with a yield of 0.18 g/g. The analysis of the genetic characteristics of an L-trp overproducing E. coli provides valuable information on L-trp synthesis and elucidates the phenotype and complex cellular properties in a high-yielding strain, which opens the possibility to transfer beneficial mutations and reconstruct an overproducer with a clean genetic background.