Expert Review of Proteomics最新文献

Introduction: The proactive identification of diseases through screening tests has long been endorsed as a means to preempt symptomatic onset. However, such screening endeavors are fraught with complications, such as diagnostic inaccuracies, procedural risks, and patient unease during examinations. These challenges are amplified when screenings for multiple diseases are administered concurrently. Selected Reaction Monitoring (SRM) offers a unique advantage, allowing for the high-throughput quantification of hundreds of analytes with minimal interferences.

Areas covered: Our research posits that SRM-based assays, traditionally tailored for single-disease biomarker profiling, can be repurposed for multi-disease screening. This innovative approach has the potential to substantially alleviate time, labor, and cost demands on healthcare systems and patients alike. Nonetheless, there are formidable methodological hurdles to overcome. These include difficulties in detecting low-abundance proteins and the risk of model overfitting due to the multiple functionalities of single proteins across different disease spectrums - issues especially pertinent in blood-based assays where detection sensitivity is constrained. As we move forward, technological strides in sample preparation, online extraction, throughput, and automation are expected to ameliorate these limitations.

Expert opinion: The maturation of mass spectrometry's integration into clinical laboratories appears imminent, positioning it as an invaluable asset for delivering highly sensitive, reproducible, and precise diagnostic results.

Introduction: The nasal cavity is the initial site of the human respiratory tract and is one of the habitats where microorganisms colonize. The findings from a growing number of studies have shown that the nasal microbiome is an important factor for human disease and health. 16S rRNA sequencing and metagenomic next-generation sequencing (mNGS) are the most commonly used means of microbiome evaluation. Among them, 16S rRNA sequencing is the primary method used in previous studies of nasal microbiomes. However, neither 16S rRNA sequencing nor mNGS can be used to analyze the genes specifically expressed by nasal microorganisms and their functions. This problem can be addressed by proteomic analysis of the nasal microbiome.

Areas covered: In this review, we summarize current advances in research on the nasal microbiome, introduce the methods for proteomic evaluation of the nasal microbiome, and focus on the important roles of proteomic evaluation of the nasal microbiome in the diagnosis and treatment of related diseases.

Expert opinion: The detection method for microbiome-expressed proteins is known as metaproteomics. Metaproteomic analysis can help us dig deeper into the nasal microbiomes and provide new targets and ideas for clinical diagnosis and treatment of many nasal dysbiosis-related diseases.

Introduction: Induced pluripotent stem (iPS) cell technology has transformed biomedical research. New opportunities now exist to create new organoids, microtissues, and body-on-a-chip systems for basic biology investigations and clinical translations.

Areas covered: We discuss the utility of proteomics for attaining an unbiased view into protein expression changes during iPS cell differentiation, cell maturation, and tissue generation. The ability to discover cell-type specific protein markers during the differentiation and maturation of iPS-derived cells has led to new strategies to improve cell production yield and fidelity. In parallel, proteomic characterization of iPS-derived organoids is helping to realize the goal of bridging in vitro and in vivo systems.

Expert opinions: We discuss some current challenges of proteomics in iPS cell research and future directions, including the integration of proteomic and transcriptomic data for systems-level analysis.

Introduction: Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation.

Areas covered: In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes.

Expert opinion: Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.

Introduction: Male infertility is a major public health concern globally. Proteomics has revolutionized our comprehension of male fertility by identifying potential infertility biomarkers and reproductive defects. Studies comparing sperm proteome with other male reproductive tissues have the potential to refine fertility diagnostics and guide infertility treatment development.

Areas covered: This review encapsulates literature using proteomic approaches to progress male reproductive biology. Our search methodology included systematic searches of databases such as PubMed, Scopus, and Web of Science for articles up to 2023. Keywords used included 'male fertility proteomics,' 'spermatozoa proteome,' 'testis proteomics,' 'epididymal proteomics,' and 'non-hormonal male contraception.' Inclusion criteria were robust experimental design, significant contributions to male fertility, and novel use of proteomic technologies.

Expert opinion: Expert analysis shows a shift from traditional research to an integrative approach that clarifies male reproductive health's molecular intricacies. A gap exists between proteomic discoveries and clinical application. The expert opinions consolidated here not only navigate the current findings but also chart the future proteomic applications for scientific and clinical breakthroughs. We underscore the need for continued investment in proteomic research - both in the technological and collaborative arenas - to further unravel the secrets of male fertility, which will be central to resolving fertility issues in the coming era.

Introduction: Development of new methods is essential to make great leaps in science, opening up new avenues for research, but the process behind method development is seldom described.

Areas covered: Over the last twenty years we have been developing several new methods, such as in situ PLA, proxHCR, and MolBoolean, using oligonucleotide-conjugated antibodies to visualize protein-protein interactions. Herein, we describe the rationale behind the oligonucleotide systems of these methods. The main objective of this paper is to provide researchers with a description on how we thought when we designed those methods. We also describe in detail how the methods work and how one should interpret results.

Expert opinion: Understanding how the methods work is important in selecting an appropriate method for your experiments. We also hope that this paper may be an inspiration for young researchers to enter the field of method development. Seeing a problem is a motivation to develop a solution.