Extracellular vesicles (EVs), present in blood as well as other biological fluids, encapsulate nucleic acid biomarkers used for diagnosis, prognosis and treatment monitoring of disease via minimally invasive liquid biopsy. EVs are a reliable source of biomarkers because their contents reflect the cells from which they are derived, and their lipid bilayer membranes protect nucleic acids from degradation. Previously, analyzing EVs in blood was difficult because of time-consuming, labor-intensive EV isolation methods. Here, we provide a protocol for an EV detection approach in which reagent-loaded liposomes fuse with EVs directly in patient blood to sensitively detect RNA within the EVs. In this ‘liposome–EV fusion assay’, antibodies capture EVs in blood, and reagent-loaded liposomes initiate liposome–EV fusion and CRISPR-based nucleic acid detection. We originally used this assay to detect EV-encapsulated viral RNA and accurately diagnose infectious diseases from patient plasma. It has since been adopted by many other research groups to detect mRNA, microRNA, DNA, DNA mutations and EV surface proteins in a variety of patient-derived tumor samples, incorporating enzymatic and nonenzymatic detection reagents and different diagnostic readouts. As a clinical and research tool, this approach has great potential for the diagnosis, treatment and study of cancer, infectious diseases and neurological dysfunction. This protocol outlines an extracellular vesicle detection approach in which reagent-loaded liposomes fuse with extracellular vesicles directly in patient blood to sensitively detect RNA within the extracellular vesicles.

Mycobacterial infections pose a significant global health concern, requiring precise identification for effective treatment. However, diagnosing them is challenging due to inaccurate identifications and prolonged times. In this study, we aimed to develop a novel peptidome-based method using mycobacterial growth indicator tube (MGIT) cultures for faster and more accurate identification. We created the PEPtide Taxonomy/ORganism CHecking (PEP-TORCH), an algorithm that analyzes tryptic peptides identified by mass spectrometry to diagnose species and subspecies with predominance scores. PEP-TORCH demonstrated 100% accuracy in identifying mycobacterial species, subspecies, and co-infections in 81 individuals suspected of mycobacterial infections, eliminating the need for a sub-solid culture procedure, the gold standard in clinical practice. A notable strength of PEP-TORCH is its ability to provide information on species and subspecies simultaneously, a process conventionally achieved sequentially. This capability significantly expedites pathogen identification. Furthermore, a targeted proteomics method was validated in 63 clinical samples using the taxa-specific peptides selected by PEP-TORCH, making them suitable as biomarkers in more clinically friendly settings. This comprehensive identification approach holds promise for streamlining treatment strategies in clinical practice.

Single-cell analysis of phenotypic plasticity could improve the development of more effective therapeutics. Still, the development of tools to measure single-cell heterogeneity has lagged due to difficulties in manipulating and culturing single cells. Here, we describe a single-cell culture and phenotyping platform that employs a starburst microfluidic network and automatic liquid handling system to capture single cells for long-term culture and multi-dimensional analysis and quantify their clonal properties via their surface biomarker and secreted cytokine/growth factor profiles. Studies performed on this platform found that cells derived from single-cell cultures maintained phenotypic equilibria similar to their parental populations. Single-cell cultures exposed to chemotherapeutic drugs stochastically disrupted this balance to favor stem-like cells. They had enhanced expression of mRNAs and secreted factors associated with cell signaling, survival, and differentiation. This single-cell analysis approach can be extended to analyze more complex phenotypes and screen responses to therapeutic targets.

Interferon-gamma release assays (IGRAs) that evaluate an individual’s T-cell activation response to Mycobacterium tuberculosis (M.tb)-specific peptides serve an important role in diagnosing tuberculosis (TB). However, there are substantial challenges to the use of IGRAs in resource-limited settings. Further, IGRA diagnostic performance can also be compromised in anergic individuals. Here we describe a microfluidic chip-based antigen-specific T-cell response assay (ASTRA) that automates the detection of M.tb-specific T-cell activation responses to facilitate screening for latent M.tb infection and TB. We observe that ASTRA demonstrates high specificity for M.tb infection in independent patient cohorts. Compared with IGRA, ASTRA shows greater diagnostic sensitivity in individuals with HIV-1 co-infections (93.8

Most CRISPR assays lack clinical utility due to their complex workflows and limited validation. Here we present a streamlined "one-pot" asymmetric CRISPR tuberculosis assay that attenuates amplicon degradation to achieve 5 copies/μL sensitivity within 60 min and detect positive patient samples within 15 min. This assay exhibited 93%, 83%, and 93% sensitivity with adult respiratory, pediatric stool, and adult cerebral spinal fluid specimens, and detected 64% of clinically diagnosed tuberculous meningitis cases, in a cohort of 603 clinical samples. This assay achieves complete specificity and greater sensitivity (74% vs. 56%) than the most sensitive reference test with prospectively collected tongue swabs, and exhibits similar performance when adapted to a lateral flow assay format and employed to analyze self-collected tongue swabs. These results demonstrate the utility of this approach across diverse specimen types, including those suitable for use in remote and resource-limited settings, to improve access to molecular diagnostics.

BACKGROUNDPneumocystis jirovecii pneumonia (PCP) is a leading cause of fungal pneumonia, but its diagnosis primarily relies on invasive bronchoalveolar lavage (BAL) specimens that are difficult to obtain. Oropharyngeal swabs and serum could improve the PCP diagnostic workflow, and we hypothesized that CRISPR could enhance assay sensitivity to allow robust P. jirovecii diagnosis using swabs and serum. Herein, we describe the development of an ultrasensitive RT-PCR-coupled CRISPR assay with high active-infection specificity in infant swabs and adult BAL and serum.METHODSMouse analyses employed an RT-PCR CRISPR assay to analyze P. murina transcripts in WT and Rag2-/- mouse lung RNA, BAL, and serum at 2-, 4-, and 6-weeks after infection. Human studies used an optimized RT-PCR CRISPR assay to detect P. jirovecii transcripts in infant oropharyngeal swab samples, adult serum, and adult BAL specimens from patients who were infected with P. jirovecii and those who were not.RESULTSThe P. murina assays sensitively detected Pneumocystis RNA in the serum of infected mice throughout infection. Oropharyngeal swab CRISPR assay results identified infants infected with P. jirovecii with greater sensitivity (96.3% versus 66.7%) and specificity (100% versus 90.6%) than RT-qPCR compared with mitochondrial large subunit rRNA gene (mtLSU) standard marker, and CRISPR results achieved higher sensitivity than RT-qPCR results (93.3% versus 26.7%) in adult serum specimens.CONCLUSIONSince swabs are routinely collected in pediatric patients with pneumonia and serum is easier to obtain than BAL, this assay approach could improve the accuracy and timing of pediatric and adult Pneumocystis diagnosis by achieving specificity for active infection and potentially avoiding the requirement for BAL specimens.FUNDINGThe work was supported by the NIH (R01AI120033), NHLBI (R35HL139930), the Louisiana Board of Regents Endowed Chairs for Eminent Scholars program, and by research funding provided by National Institute of Allergy and Infectious Diseases (NIAID) (R01AI144168, R01AI175618, R01AI173021). This research was also funded by the NIHR (project 134342) using UK aid from the UK government to support global health research.

Rapid portable assays are needed to improve diagnosis, treatment, and reduce transmission of tuberculosis (TB), but current tests are not suitable for patients in resource-limited settings with high TB burden. Here we report a low complexity, lab-in-tube system that is read by an integrated handheld device that detects Mycobacterium tuberculosis (Mtb) DNA in blood and respiratory samples from a variety of clinical settings. This microprocessor-controlled device uses an LCD user interface to control assay performance, automate assay analysis, and provide results in a simple readout. This point-of-care single-tube assay uses a DNA enrichment membrane and a low-cost cellulose disc containing lyophilized recombinase polymerase amplification and CRISPR-Cas12a reagents to attain single-nucleotide specificity and high sensitivity within 1 hour of sample application, without a conventional DNA isolation procedure. Assay results obtained with serum cell-free DNA isolated from a cohort of children aged 1 to 16 years detected pulmonary and extrapulmonary TB with high sensitivity versus culture and GeneXpert MTB/RIF results (81% versus 55% and 68%) and good specificity (94%), meeting the World Health Organization target product profile criteria for new nonsputum TB diagnostics. Changes in assay results for serum isolated during treatment were also highly predictive of clinical response. Results obtained with noninvasive sputum and saliva specimens from adults with bacteriologically confirmed pulmonary TB were also comparable to those reported for reference methods. This rapid and inexpensive lab-in-tube assay approach thus represents one means to address the need for point-of-care TB diagnostics useable in low-resource settings.

The ongoing monkeypox virus outbreak highlights the need for rapid and accurate diagnostics to enhance epidemic control. CRISPR-based assays hold promise, but clinical translation is hindered by high complexity and low throughput. Here, we describe a thermally regulated asynchronous CRISPR-enhanced (TRACE) assay that rapidly and sensitively detects multiple DNA targets in a streamlined, one-pot format. TRACE exhibits a 2.5 copies/test limit of detection - 40 times lower than a canonical one-pot CRISPR. When applied to clinical samples, it achieves 99.5% accuracy across diverse sample types, and can detect MPXV within 11 minutes. Point-of-care TRACE assays meet ASSURED criteria and deliver comparable performance to qPCR, with a fivefold reduced report time, in outpatient settings. Moreover, TRACE enables simultaneous detection of pathogen and host genes at comparable sensitivity to address a critical limitation of current CRISPR assays, which lack internal controls. TRACE thus enables rapid, on-site surveillance to facilitate bench-to-bedside translation of CRISPR diagnostics.

Rationale: Myocardial injury is a common and life-threatening complication of severe acute pancreatitis (SAP) and is driven primarily by metabolic disturbances. This study aimed to elucidate the pathogenesis of SAP-induced cardiac injury (SACI) and to identify effective therapeutic strategies. Methods: Untargeted metabolomics and proteomics analyses were employed to identify metabolic pathways and proteins associated with myocardial injury in SACI mouse model. Histological and Western blot assays were used to assess lipid droplet (LD) accumulation, the expression of autophagy markers, and LD-autophagosome colocalization. The traditional Chinese medicine formula Taohong Siwu Decoction (THSWD) was tested for its therapeutic potential in a SACI mouse model and a SACI cardiomyocyte model established by incubating primary mouse cardiomyocytes with serum from the SACI mouse model. These SACI cardiomyocytes cultures were then treated with serum from control or THSWD-treated mice, with or without autophagy inhibitors, and analyzed for effects on lipophagy, mitochondrial structure and function, long-chain fatty acid metabolism, and oxidative stress. Results: SAP-induced myocardial injury was characterized by disrupted lipid metabolism, leading to abnormal cardiomyocyte LD accumulation and structural and functional deficiencies in their mitochondria. THSWD treatment reduced LD accumulation, restored LD-autophagosome colocalization, and increased mitochondrial structural integrity, membrane potential, and fatty acid β-oxidation. However, these THSWD effects were abolished in the presence of an autophagy inhibitor, implying they occur via a lipophagy-dependent mechanism. Conclusion: Excessive LD accumulation drives mitochondrial dysfunction, contributing to SAP-induced myocardial lipotoxicity. THSWD promotes lipophagy to mitigate lipid accumulation and restore mitochondrial function, and may serve as an effective therapeutic strategy for SAP-induced cardiac metabolic disorders and mitochondrial dysfunction.

Objectives Pediatric tuberculosis (TB) diagnosis is complicated by challenges in obtaining invasive respiratory specimens that frequently contain few Mycobacterium tuberculosis (Mtb) bacilli. We report the diagnostic performance of an Mtb antigen-derived peptide (MAP-TB) assay and its ability to monitor TB treatment response. Methods Study cohorts enrolled children who presented with presumptive TB at two hospitals in South Africa from 2012 to 2017 (157 children aged <13 years) and at community-based clinics in the Dominican Republic from 2019 to 2023 (101 children aged <18 years). Children were evaluated for TB at enrollment and six months post-enrollment and assigned confirmed, unconfirmed, or unlikely TB diagnoses using the 2015 NIH diagnostic criteria for pediatric TB. MAP-TB assay performance was evaluated using serum collected at baseline and at regular intervals post-enrollment following STARD guidelines. Results MAP-TB sensitivity for confirmed and unconfirmed TB was comparable to culture and Xpert sensitivity for confirmed TB, but MAP-TB specificity revealed age-dependence, decreasing from 98·1% to 78·4%, when including children aged <1 year. MAP-TB values decreased by six months post-treatment initiation in children with symptom improvement. Conclusions Serum MAP-TB results can effectively diagnose pediatric TB, including unconfirmed and extrapulmonary TB missed by current methods, and correspond to effective treatment.

New solutions are needed to detect genotype-phenotype associations involved in microbial drug resistance. Herein, we describe a Group Association Model (GAM) that accurately identifies genetic variants linked to drug resistance and mitigates false-positive cross-resistance artifacts without prior knowledge. GAM analysis of 7,179 Mycobacterium tuberculosis (Mtb) isolates identifies gene targets for all analyzed drugs, revealing comparable performance but fewer cross-resistance artifacts than World Health Organization (WHO) mutation catalogue approach, which requires expert rules and precedents. GAM also reveals generalizability, demonstrating high predictive accuracy with 3,942 S. aureus isolates. GAM refinement by machine learning (ML) improves predictive accuracy with small or incomplete datasets. These findings were validated using 427 Mtb isolates from three sites, where GAM inputs are also found to be more suitable in ML prediction models than WHO inputs. GAM + ML could thus address the limitations of current drug resistance prediction methods to improve treatment decisions for drug-resistant microbial infections. In this work, authors describe a Group Association Model (GAM) that detects genotype phenotype associations in microbial drug resistance; refined with the machine learning, it identifies features for predictive modelling, reducing cross-resistance artifacts and potentially improving treatment decisions.

Improved sanitation, increased access to health care, and advances in preventive and clinical medicine have reduced the mortality and morbidity rates of several infectious diseases. However, recent outbreaks of several emerging infectious diseases (EIDs) have caused substantial mortality and morbidity, and the frequency of these outbreaks is likely to increase due to pathogen, environmental, and population effects driven by climate change. Extreme or persistent changes in temperature, precipitation, humidity, and air pollution associated with climate change can, for example, expand the size of EID reservoirs, increase host-pathogen and cross-species host contacts to promote transmission or spillover events, and degrade the overall health of susceptible host populations leading to new EID outbreaks. It is therefore vital to establish global strategies to track and model potential responses of candidate EIDs to project their future behaviour and guide research efforts on early detection and diagnosis technologies and vaccine development efforts for these targets. Multi-disciplinary collaborations are demanding to develop effective inter-continental surveillance and modelling platforms that employ artificial intelligence to mitigate climate change effects on EID outbreaks. In this review, we discuss how climate change has increased the risk of EIDs and describe novel approaches to improve surveillance of emerging pathogens that pose the risk for EID outbreaks, new and existing measures that could be used to contain or reduce the risk of future EID outbreaks, and new methods to improve EID tracking during further outbreaks to limit disease transmission.

Background: Respiratory syncytial virus (RSV) is the most common cause of lower respiratory tract infection (LRTI) in infancy and early childhood. Accurate diagnosis is essential to assess the true extent of RSV prevalence in the community and implement new preventative and therapeutic strategies effectively. Methods: RSV cell-free RNA (cfRNA) levels were measured in subjects with or without RSV-LRTI and mother/baby dyads infected in pregnancy. Diagnostic performance was first tested in nasopharyngeal (NP) swabs and serum specimens from two cohorts. Then, serum RSV-cfRNA levels from mother/baby dyads were used to investigate RSV transplacental transmission. Findings: A CRISPR-RSV assay detected RSV-cfRNA in NP swabs of RSV-infected subjects with 100% (95% CI: 91·0–100%) sensitivity and 100% (95% CI: 88·8–100%) specificity and in serum of RSV-infected children with 80·0 (95% CI: 44·4–97·5%) sensitivity and 100% (95% CI: 47·8–100%) specificity. CRISPR-RSV measurements of maternal and cord blood RSV-cfRNA levels correlated with the respective ddPCR results. Interpretation: This study validates a new CRISPR-based assay that rapidly detects RSV in respiratory secretions and serum samples with high specificity and sensitivity and is particularly useful in diagnosing congenital RSV infection. Funding: Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Allergy and Infectious Diseases, U.S. Department of Defense, National Institute of Neurological Disorders and Stroke, and National Cancer Institute. Declaration of Interest: We declare no competing interests. Ethical Approval: All study participants in the NCH and TTRSV cohorts were enrolled according to protocols approved by the Human Subjects Institutional Review Boards at Tulane University (TTRSV cohort) or Nationwide Children’s Hospital (NCH cohort). All participants or their legal guardians provided written informed consent.

New point-of-care tests (POCTs), which are especially useful in low-resource settings, are needed to expand screening capacity for diseases that cause significant mortality: tuberculosis, multiple cancers, and emerging infectious diseases. Recently, clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostic (CRISPR-Dx) assays have emerged as powerful and versatile alternatives to traditional nucleic acid tests, revealing a strong potential to meet this need for new POCTs. In this review, we discuss CRISPR-Dx assay techniques that have been or could be applied to develop POCTs, including techniques for sample processing, target amplification, multiplex assay design, and signal readout. This review also describes current and potential applications for POCTs in disease diagnosis and includes future opportunities and challenges for such tests. These tests need to advance beyond initial assay development efforts to broadly meet criteria for use in low-resource settings.

Extracellular vesicles (EVs) secreted by all cell types are involved in the cell-to-cell transfer of regulatory factors that influence cell and tissue phenotypes in normal and diseased tissues. EVs are thus a rich source of biomarker targets for assays that analyze blood and urinary EVs for disease diagnosis. Sensitive biomarker detection in EVs derived from specific cell populations is a key major hurdle when analyzing complex biological samples, but innovative approaches surveyed in this Perspective can streamline EV isolation and enhance the sensitivity of EV detection procedures required for clinical application of EV-based diagnostics and therapeutics, including nanotechnology and microfluidics, to achieve EV characterizations. Finally, this Perspective also outlines opportunities and challenges remaining for clinical translation of EV-based assays.

Targeted mass spectrometry (MS) holds promise for precise protein and protein‐representative peptide identification and quantification, enhancing disease diagnosis. However, its clinical application is hindered by complex data analysis and expert review requirements. It is hypothesized that machine learning (ML) models can automate data analysis to accelerate the clinical application of MS. The approach involves an ML‐driven pipeline that extracts statistical and morphological features from an MS target region and feeds these features into ML algorithms to generate and assess predictive models. The findings demonstrate ML prediction models exhibit superior performance when trained on extracted features versus raw spectra intensity data and that random forest models exhibit robust classification performance in both internal and external validation datasets. These models remain effective across varying training dataset sizes and positive sample rates and are enhanced by a nested active learning approach. This approach can thus revolutionize clinical MS applications.

Rationale: Mycobacterium avium complex (MAC) is the most common cause of nontuberculous mycobacterial (NTM) pulmonary disease (PD), which exhibits increasing global incidence. Current microbiologic methods routinely used in clinical practice lack sensitivity and have long latencies, leading to delays in diagnosis and treatment initiation and evaluation. A clustered regularly interspaced short palindromic repeats (CRISPR)-based assay that measures MAC cell-free DNA (cfDNA) concentrations in serum could provide a rapid means to detect MAC infection and monitor response to antimicrobial treatment. Objectives: To develop and optimize a CRISPR MAC assay for MAC infection detection and to evaluate its diagnostic and prognostic performance in two MAC disease cohorts. Methods: MAC cfDNA serum concentrations were measured in individuals with diagnoses of MAC disease or who had bronchiectasis or chronic obstructive pulmonary disease diagnoses without histories of NTM PD or NTM-positive sputum cultures. Diagnostic performance was analyzed using pretreatment serum from two cohorts. Serum MAC cfDNA changes during MAC PD treatment were evaluated in a subset of patients with MAC PD who received macrolide-based multidrug regimens. Measurements and Main Results: The CRISPR MAC assay detected MAC cfDNA in MAC PD with 97.6% (91.6-99.7%) sensitivity and 97.6% (91.5-99.7%) specificity overall. Serum MAC cfDNA concentrations markedly decreased after MACdirected treatment initiation in patients with MAC PD who demonstrated MAC culture conversion. Conclusions: This study provides preliminary evidence for the utility of a serum-based CRISPR MAC assay to rapidly detect MAC infection and monitor the response to treatment.

Tuberculosis (TB) remains a major underdiagnosed public health threat worldwide, being responsible for more than 10 million cases and one million deaths annually. TB diagnosis has become more rapid with the development and adoption of molecular tests, but remains challenging with traditional TB diagnosis, but there has not been a critical review of this area. Here, we systematically review these approaches to assess their diagnostic potential and issues with the development and clinical evaluation of proposed CRISPR-based TB assays. Based on these observations, we propose constructive suggestions to improve sample pretreatment, method development, clinical validation, and accessibility of these assays to streamline future assay development and validation studies.

Interferon-gamma release assays (IGRAs) that measure pathogen-specific T-cell response rates can provide a more reliable estimate of protection than specific antibody levels but have limited potential for widespread use due to their workflow, personnel, and instrumentation demands. The major vaccines for SARS-CoV-2 have demonstrated substantial efficacy against all of its current variants, but approaches are needed to determine how these vaccines will perform against future variants, as they arise, to inform vaccine and public health policies. Here we describe a rapid, sensitive, nanolayer polylysine-integrated microfluidic chip IGRA read by a fluorescent microscope that has a 5 h sample-to-answer time and uses ∼25 μL of a fingerstick whole blood sample. Results from this assay correlated with those of a comparable clinical IGRA when used to evaluate the T-cell response to SARS-CoV-2 peptides in a population of vaccinated and/or infected individuals. Notably, this streamlined and inexpensive assay is suitable for high-throughput analyses in resource-limited settings for other infectious diseases.

Neurologic manifestations are among the most frequently reported complications of COVID-19. However, given the paucity of tissue samples and the highly infectious nature of the etiologic agent of COVID-19, we have limited information to understand the neuropathogenesis of COVID-19. Therefore, to better understand the impact of COVID-19 on the brain, we used mass-spectrometry-based proteomics with a data-independent acquisition mode to investigate cerebrospinal fluid (CSF) proteins collected from two different nonhuman primates, Rhesus Macaque and African Green Monkeys, for the neurologic effects of the infection. These monkeys exhibited minimal to mild pulmonary pathology but moderate to severe central nervous system (CNS) pathology. Our results indicated that CSF proteome changes after infection resolution corresponded with bronchial virus abundance during early infection and revealed substantial differences between the infected nonhuman primates and their age-matched uninfected controls, suggesting these differences could reflect altered secretion of CNS factors in response to SARS-CoV-2-induced neuropathology. We also observed the infected animals exhibited highly scattered data distributions compared to their corresponding controls indicating the heterogeneity of the CSF proteome change and the host response to the viral infection. Dysregulated CSF proteins were preferentially enriched in functional pathways associated with progressive neurodegenerative disorders, hemostasis, and innate immune responses that could influence neuroinflammatory responses following COVID-19. Mapping these dysregulated proteins to the Human Brain Protein Atlas found that they tended to be enriched in brain regions that exhibit more frequent injury following COVID-19. It, therefore, appears reasonable to speculate that such CSF protein changes could serve as signatures for neurologic injury, identify important regulatory pathways in this process, and potentially reveal therapeutic targets to prevent or attenuate the development of neurologic injuries following COVID-19.