Annual review of analytical chemistry (Palo Alto, Calif.)最新文献

Mass spectrometry-based proteomics and metaproteomics have long been used in the study of human microbiomes, with the potential of metaproteomics only recently being fully harnessed. This progress is due to the advancements of high-performance mass spectrometers, innovative proteomics strategies, and the development of dedicated bioinformatics tools. In this review, we critically examine the recent technological developments that enhance the application of metaproteomics in clinical microbiome analysis. We also summarize significant advancements in the application of metaproteomics to study human microbiomes across various body sites under disease conditions. Despite these, the potential of metaproteomics remains underutilized due to typically small sample sizes and insufficient data mining. We thereby highlight some key aspects that could facilitate the broader and more effective application of mass spectrometry-based metaproteomics in clinical microbiome analysis, including the development of microbiome assays for translational research and application.

Mass spectrometry (MS)-based top-down proteomics (TDP) characterizes proteoforms in cells, tissues, and biological fluids (e.g., human plasma) to better our understanding of protein function and to discover new protein biomarkers for disease diagnosis and therapeutic development. Separations of proteoforms with high peak capacity are needed due to the high complexity of biological samples. Capillary electrophoresis (CE)-MS has been recognized as a powerful analytical tool for protein analysis since the 1980s owing to its high separation efficiency and sensitivity of CE-MS for proteoforms. Here, we review benefits of CE-MS for advancing TDP, challenges and solutions of the method, and the main research areas in which CE-MS-based TDP can make significant contributions. We provide a brief perspective of CE-MS-based TDP moving forward.

Comprehensive two-dimensional liquid chromatography (LC×LC) is increasingly being used to provide new information on the composition of complex samples. More widespread use of the technique is, however, hampered by the complexity of method development, which involves the selection and optimization of a very large number of experimental variables while considering their interdependence and relationship with conflicting analysis goals. This contribution summarizes the progress made in online LC×LC method development to date. Recent trends in advanced method optimization are highlighted to demonstrate how progress in the field enables the development of highly efficient LC×LC methods.

The article profiles 11 academic analytical chemists and explores the impact of their unique backgrounds and identities on their creativity and contributions to the field. The narratives provide inspiration and a reminder of the humanity of those contributing to innovation in analytical chemistry. Arranged alphabetically by last name, these innovators are Abraham Badu-Tawiah, Karl Booksh, Luis A. Colón, Purnendu (Sandy) Dasgupta, Jani C. Ingram, Lisa M. Jones, Matthew Lockett, Shelley Minteer, Renã A.S. Robinson, Joaquín Rodríguez-López, and Isiah M. Warner.

Photoelectrochemical (PEC) sensing based on chemical or biological recognition has received a tremendous amount of attention in recent years, providing analytical chemists a plethora of opportunities. However, emerging techniques and unknown processes in this field remain unexplored. We summarize the recently reported PEC sensing methods. First, we briefly describe the basic principles and technical characteristics of PEC sensing. Next, we highlight the application of various materials, nucleic acids, and other strategies for amplifying PEC signals. Finally, we discuss the current state of knowledge regarding the realization of miniaturized equipment during PEC sensor manufacturing. Summarizing the technological advances and research breakthroughs in PEC sensing over time can help increase the quality of follow-up research.

Electrochemical biosensors have emerged as pivotal tools in point-of-care (POC) sensing, offering rapid, sensitive, and cost-effective detection platforms. Different strategies for advancing electrochemical POC biosensors have been explored recently, including fabrication methodologies and advances in biorecognition elements. This review comprehensively explores the miniaturization and integration of portable and wireless devices into fully integrated systems, highlighting recent advancements and challenges in fabrication techniques. We also discuss different enhancement strategies for biorecognition in POC testing, including immunosensors, aptasensors, genosensors, and CRISPR-based biosensors, evaluating their respective strengths and applications. Furthermore, this review addresses the complexity of multiplexing within electrochemical biosensing platforms. Finally, we outline some critical considerations for field deployment and commercialization of electrochemical POC biosensors. We aim to provide a comprehensive overview of advancing electrochemical biosensors toward robust and scalable POC solutions by synthesizing advancements across this emerging field.

The design and implementation of biomedical devices for both diagnostic and direct medical applications have revolutionized patient care, paving the way for improved patient outcomes. Understanding the characteristics of materials used in the design of new devices is essential for their advancement. In this review, our goal is to assist biomedical researchers in appreciating the importance of these properties and the role of selecting the proper measurement. We discuss how the nanoscopic molecular composition, arrangement, and interactions generate the properties of liquids, solids, viscoelastic materials, and colloids and discuss the measurement techniques that can be used to assess these properties from the nanoscale to the macroscale. We explore the linear and nonlinear mechanical responses of materials, elucidate their behaviors under varying conditions, and discuss corresponding measurement techniques. Finally, we highlight the importance of tailoring measurements to the underlying biological processes and applications being investigated.

Protein glycosylation, the covalent attachment of carbohydrate, or glycan, structures onto the protein backbone, is one of the most complex and heterogeneous post-translational modifications (PTMs). Extracellular protein glycosylation, in particular N- and mucin-type O-glycosylation, plays pivotal roles in a number of biophysical and biochemical processes, such as protein folding and stability, cell adhesion, signaling, and protection. As such, aberrant glycosylation is implicated in a variety of diseases, including cancer. However, the nontemplated nature and structural heterogeneity of protein glycosylation hinder glycoprotein characterization with traditional methods. Recent advances in analytical techniques have improved capabilities for decoding glycan complexity, a promising step toward understanding the role of glycosylation in human health and disease. In this review, we highlight key and emerging techniques to study protein glycosylation, and we emphasize how these techniques have improved our understanding of glycosylation in a biologically relevant context.

Forensic analytical chemistry has evolved significantly, embracing myriad methodological and technological advancements to expand the frontiers of evidence analysis. Beyond technology, modern forensic scientists face challenges working within the criminal justice system where scientific operational and research choices are directed by law enforcement agencies. This review examines issues surrounding the accuracy of presumptive tests, the use of portable instrumentation, and sample contamination, as exemplified by field drug testing. Data management and preservation are discussed, including the integration of machine learning into forensic workflows and the critical need for transparency to stakeholders. Finally, the operational interpretation and translation of analytical results and the role of forensic laboratories as high-reliability organizations are explored. Addressing the disparities and ensuring the credibility of forensic methods are essential for promoting reliability and equity within the justice system.

Tandem mass spectrometry (MS/MS) is crucial for small-molecule analysis; however, traditional computational methods are limited by incomplete reference libraries and complex data processing. Machine learning (ML) is transforming small-molecule mass spectrometry in three key directions: (a) predicting MS/MS spectra and related physicochemical properties to expand reference libraries, (b) improving spectral matching through automated pattern extraction, and (c) predicting molecular structures of compounds directly from their MS/MS spectra. We review ML approaches for molecular representations [descriptors, simplified molecular-input line-entry (SMILE) strings, and graphs] and MS/MS spectra representations (using binned vectors and peak lists) along with recent advances in spectra prediction, retention time, collision cross sections, and spectral matching. Finally, we discuss ML-integrated workflows for chemical formula identification. By addressing the limitations of current methods for compound identification, these ML approaches can greatly enhance the understanding of biological processes and the development of diagnostic and therapeutic tools.