Advances in protein sequencing and analysis are poised to transform proteomics through an ability to link sequence, structure, and function at scale, thereby accelerating biological discovery and biomedical innovation. However, interrogating proteins is uniquely challenging because they cannot be amplified, are composed of complex chemical structures, and exist across a vast landscape of proteoforms. Techniques such as mass spectrometry typically drive large-scale proteomics studies; however, a new generation of technologies is pushing the boundaries, promising new features such as de novo, single-molecule, and/or higher-throughput sequencing and analysis. While many strategies are still in an early stage, a few modalities, such as fluorosequencing, single-molecule sequencing, digital proteomics mapping, and nanopore-based protein sequencing, have now reached or are thought to be nearing commercial implementation. In this review, we evaluate the mechanisms, current progress, and remaining challenges of these technologies while also highlighting how recent innovations are converging toward a new generation of proteomic technologies.
Diagnostics are central to pandemic preparedness, guiding surveillance, clinical care, and public health response. The COVID-19 pandemic exposed limitations in diagnostic infrastructure but also accelerated innovation across assay types, created accessible testing mechanisms, and demonstrated the value of public-private partnerships. This review outlines the critical roles diagnostics play across pandemic phases, from early detection to post recovery surveillance. We review the current diagnostic landscape for pandemic priority pathogens and unmet needs and challenges and examine recent advances in analytical technologies, including isothermal amplification, CRISPR-based methods, alternative sample types, and novel platforms, with a focus on their potential for rapid deployment and field use. We also explore the emergence of diagnostic accelerators and biorepositories that support assay validation and global test availability. For analytical chemists, pandemic preparedness presents a call to action: to develop, validate, and translate innovative tools that can adapt to meet urgent diagnostic needs during future health emergencies.
The rapid and continued development of mass spectrometry-based technologies has significantly increased the capability to study and characterize lipids while providing new insight into the complex roles of lipids throughout biology. These capabilities have included the ability to quantify, structurally characterize (including resolving isomers that pose significant challenges to lipidomics), and spatially map lipids within numerous complex organisms, revealing new capabilities in emerging areas such as single-cell analysis. With these rapid developments, several challenges have emerged, such as accurate lipid identification, incorrect and overinterpretation of mass spectrometry data and structural assignments, and the need for improved analytical and bioinformatics tools to understand lipidomics data at the pathway and systems levels. This review critically assesses analytical technologies used for lipidomics studies, along with current challenges and technological developments driving the field forward. By highlighting these challenges, and possible avenues to address them, this review emphasizes the excitement for the future of lipidomics and the need for continued development of analytical tools to enhance our understanding of lipid biology.
Gas-phase ion-ion reactions lead to well-defined changes in mass and charge that are readily detected via mass spectrometry. They have unusually large cross sections, which allow for rates on the order of 1-1,000 s-1 and, as a result, enable a variety of analytically useful measurements. Such applications rely on one or more of a variety of reaction mechanisms, such as proton transfer, electron transfer, metal ion transfer, and selective covalent bond formation. Electrodynamic ion traps make excellent reaction vessels for ion-ion reactions due to their ability to trap one or both polarities of ions, thereby allowing reactions to proceed with high reactant to product conversion. Understanding the underlying phenomena of ion-ion reactions, as well as the conditions under which they proceed, is essential to designing future experiments. This tutorial review summarizes the underlying phenomena of gas-phase ion-ion reactions and related practical considerations needed to optimize these reactions in an electrodynamic ion trap.
Metabolic function plays a key role in our understanding of both biological and pathophysiological processes. Metabolism is a complex combination of intrinsic processes and environmental cues across a heterogeneous mix of cell types. To investigate metabolism, stable isotope tracing is a versatile approach to assess metabolism across scales, including in cultured cells, animal models, and humans. From the first tracing studies over a century ago, the development and utility of these studies have gone hand-in-hand with technological advances in detecting these labeled atoms, particularly with mass spectrometry. In this review, we describe the instrumentation used to measure isotopically labeled metabolites and approaches to analyze and interpret stable isotope tracing data, and discuss current challenges and opportunities for discovery with these methods.
Extracellular vesicles (EVs) are membrane-bound vesicles that mediate intercellular communication and have gained significant interest as potential biomarker sources and therapeutic agents. This review summarizes the most recent advances in EV analysis, including an overview of EV biology, current approaches for EV isolation and enrichment, and emerging technologies for EV detection, with a particular focus on single-EV analysis. We also examine the integration of artificial intelligence into EV research. This review provides a broad perspective into the landscape of EV analysis and highlights potential future directions in this rapidly evolving field to improve the analytical rigor and translational potential of EV-based diagnostics and therapeutics.
Autonomous systems integrating machine learning (ML) and laboratory automation are transforming synthetic chemistry by enabling closed-loop experimentation and discovery. In this review, we examine the state-of-the-art in autonomous systems for organic synthesis, with a focus on the components, configurations, and ML algorithms that enable automated reaction planning, execution, and optimization. We survey representative systems that span applications from reaction discovery to molecular optimization, comparing flow and batch configurations and identifying trends in system design. Emphasis is placed on the critical bottlenecks of purification and analytical measurement, particularly structural elucidation of unexpected products-areas that currently constrain autonomous platforms. We describe recent advances in chromatographic method development, structural elucidation from mass spectrometry and nuclear magnetic resonance, and novel ML-based approaches to quantify complex mixtures without calibration. By focusing on enabling technologies in chemical analysis, we identify opportunities for ML and automation to expand beyond domain-specific platforms and accelerate the pace of synthetic discovery.
Mental health disorders, such as depression, represent a growing global challenge. Depression is difficult to diagnose and treat. These difficulties stem from an insufficient understanding of the underlying mechanisms of the disorder. It is incredibly challenging to improve diagnostic and therapeutic approaches without a clear understanding of depression pathology. Neurotransmitters are low in concentration and fluctuate rapidly, making them difficult to investigate. Progress in methods to study the brain has uncovered clues to the pathology of depression and antidepressant mechanisms. In this review, we first describe the three medical hypotheses of depression: the monoamine, plasticity, and inflammation theories. We highlight key analytical methods that have been employed in depression studies. Lastly, we show how these investigations have advanced our knowledge of depression mechanisms and treatment strategies. Thus, via this review, we present the status quo of how chemical measurements are guiding our understanding of the chemical underpinnings of depression and pointing the community toward new antidepressant treatment targets.
Single-cell proteomics (scP) is a crucial complement to transcriptomics, offering deeper insight into cellular heterogeneity, disease mechanisms, and therapeutic vulnerabilities in samples such as 2D cell culture, 3D models, and patient tissue. While transcriptomics enables high-throughput gene expression characterization, RNA levels frequently do not correlate with protein levels even in the same cell. Furthermore, protein isoforms, posttranslational modifications, and complexes are missed by transcriptomic analyses. This review explores modern scP technologies, including flow and mass cytometry, single-cell mass spectrometry, immunohistochemistry, cyclic imaging, and imaging mass cytometry applied to both dissociated and spatially preserved samples. We emphasize applying these techniques to organ-on-a-chip, organoids, spheroids, and intact tissues, highlighting advances in spatial resolution and multiplexing. We also discuss the trade-offs between throughput, spatial fidelity, and protein selectivity across platforms. Finally, we identify key measurement gaps, suggesting future directions toward spatially resolved scP clinical translation.
Hyaluronan (HA) is an essential polysaccharide found throughout nature where it serves diverse biological roles in a broad range of fundamental biological processes and diseases. A critical aspect of HA is its molecular weight (MW), which varies from a few disaccharides to polymers tens of megadaltons in length. Because the behavior of HA depends distinctly on size, there is great interest in the accurate determination of its MW distribution in different conditions. A solution is presented by the solid-state nanopore platform in which HA molecules are probed individually as they pass electrically through a fabricated pore. The approach has been built into a sensitive and quantitative tool for HA MW assessment through process optimization and coupling with specific HA extraction protocols. These developments have enabled it to be applied to several outstanding biological questions, including the emergent role of heavy chain-modified HA.
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.
Human skin emits a continuous flux of volatile compounds reflecting various metabolic processes in the body, microbial activity, and environmental factors. Harnessing this emission for diagnostics is of great interest given the noninvasive, passive, and accessible nature of the emission, and there is much research underway to understand the value of this skin-emitted volatile organic compound (VOC) matrix. In parallel to this, wearable skin VOC sensors are emerging and garnering attention due to their potential to provide noninvasive, real-time information for monitoring human health, overcoming many of the design challenges related to biofluid monitoring via wearables. The projected opportunities for skin VOCs are fueling innovations in wearable VOC monitoring. This review discusses the most recent developments, from fully integrated wearable skin VOC sensors that exploit existing semiconductor technology to the design and preparation of advanced new sensing materials and devices to deliver new modalities for wearable skin VOC sensors. We articulate the challenges, limitations, and opportunities for technological advances to provide a perspective on promising directions for future developments.
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.
Sample treatment plays a crucial role in ensuring accurate analysis of contaminants in aqueous, gaseous, and solid matrices. Emerging contaminants such as microplastics and poly- and perfluoroalkyl substances pose challenges due to their ubiquity and potential adverse effects on the environment and human health. By setting stringent guidelines, environmental protection agencies drive research and innovation in analytical methodologies. However, current reference methods are based on traditional techniques with a high use of chemicals and considerable waste generation. This review highlights the importance of advanced techniques, including solid-phase extraction and microextraction methods, enhanced by novel materials, for preparing environmental samples. Additionally, it discusses innovative formats and devices, such as drone-based systems and three-dimensional-printed devices, which are expanding the scope of environmental monitoring. This review aims to provide a comprehensive overview of trends and advances in sample preparation for environmental analysis over the past five years, offering insights into progress made and future directions.
Mass spectrometry (MS) has become an indispensable tool for the detailed chemical analysis of materials used in energy production, spanning both traditional fossil fuels and modern renewable alternatives. This review explores advanced ionization sources and ultrahigh-resolution MS technologies in analyzing energy materials such as petroleum, biomass, biofuels, and bio-oil. Highlighted ionization techniques include electrospray ionization, atmospheric pressure chemical ionization, atmospheric pressure photoionization, laser desorption/ionization, and matrix-assisted laser desorption/ionization, all crucial for qualitative and quantitative assessments, as well as ultrahigh-resolution Fourier transform ion cyclotron resonance and Orbitrap mass analyzers. This review underscores the remarkable compositional detail achievable with state-of-the-art MS systems, providing molecular-level insights vital for advancing energy sectors. Introducing the concept of harvesting MS, we illustrate how these techniques can overcome challenges and optimize energy operations. Through case studies, this article highlights how these insights enhance energy production efficiency and sustainability, paving the way for future innovations.
Over the past three decades, soft X-ray tomography (SXT) has rapidly evolved from a proof-of-concept microscopy method into a high-throughput quantitative imaging modality. This advancement enables researchers to address central questions in cell biology. Despite its relatively short developmental period compared to light and electron microscopy, SXT has emerged as a powerful imaging technology. It enables measuring chemical changes in cellular organelles, analyzing three-dimensional structures of whole cells and creating digital cellular models to study cell motility. We discuss the unique nature of SXT to visualize cells without fixation or labeling, enabling quantitative analyses of organelle chemical composition. We explore SXT microscopes available worldwide, SXT segmentation software, and the diverse cell types studied using this technique. We conclude with emerging directions in SXT imaging, including a brief discussion of recent discoveries that are highly influential and likely to become integral to cell biology textbooks.
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.
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.
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.
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.
