Biology subjects

Patel, L.

Publications and source records attributed to Patel, L..

18 recordsLinked to original sources

bioRxiv2026

Genome-resolved ecology and evolution of the microbiome enabled by quantitative long-read metagenomics

Standard metagenomics resolves microbial communities only in relative terms and at coarse taxonomic resolution, obscuring how individual strains change in absolute abundance and evolve within a host. We present long-read quantiomics (LRQ), a quantitative metagenomics platform coupling long-read sequencing with plasmid-based internal standards to recover high-quality genomes, including from degraded or low-input stool, and measure absolute, genome-resolved strain abundances. We validate LRQ using large plasmid standards and bacterial spike-ins, then apply it to eight years of dense sampling from an individual with colonic Crohn's disease. LRQ resolves co-resident strains of the same species following opposing trajectories with inflammation. Escherichia coli, long treated as a single pathobiont, separates into two sub-populations with opposing inflammation responses; the inflammation-associated lineage carries an immune-evasion module of virulence-associated metal-acquisition, biofilm, capsule and toxin genes. We observe genome-wide adaptive sweeps on timescales matched to disease incidence. LRQ therefore converts long-read metagenomics from a genome-recovery tool into a quantitative framework providing absolute, strain-level measurement of microbial ecology and evolution.

microbiology↗

bioRxiv2026

Discrepancies between ChIP-seq and CUT&Tag histone mark profiles are explained by GC content and chromatin accessibility

Chromatin profiling methods, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), are used to characterize the genomic localization of DNA-associated proteins. While ChIP and ChIP-seq have been used for decades, an orthogonal approach, CUT&Tag (Cleavage Under Targets and Tagmentation), is gaining popularity as an efficient and cost-effective alternative. Although previous comparative studies note discrepancies in signal-to-noise ratios and detection bias at certain genomic regions, many differences between ChIP-seq and CUT&Tag results remain largely unreconciled. Here, we systematically investigate the disagreeing signals captured by these two methods across well annotated genomic regions. We assess multiple histone mark profiles generated by different groups in two cell lines (K562 and MCF-7). Overall, our analysis indicates that compared to ChIP-seq, CUT&Tag may have limited sensitivity in low-GC environments and, as previously observed, increased signal in hyper-accessible chromatin. Notably, within GC-poor regions of active gene bodies and Polycomb-repressed domains, CUT&Tag exhibits a loss of H3K36me3 and H3K27me3 signal, respectively, where occupancy of these histone marks is otherwise expected. Further, active promoters with discrepant H3K4me3 and H3K27ac signal between the two assays differ systematically in GC content and chromatin accessibility. Promoters differentially enriched for CUT&Tag signal relative to ChIP-seq generally show higher, broader GC-content profiles and higher DNase-seq and ATAC-seq signal, while promoters enriched for ChIP-seq signal harbor the opposite characteristics. A local bias for high GC content and/or chromatin accessibility in CUT&Tag may also explain its differing signal patterns at nucleosome-depleted regions (NDRs) compared to ChIP-seq and MNase-seq promoter profiles. Altogether, our results highlight that studies focused on profiling the intensity and structure of histone modification occupancy can be sensitive to potential biases of CUT&Tag to GC content and chromatin accessibility. These characteristics should be accounted for when selecting a chromatin profiling approach, analyzing and interpreting data as well as drawing biological conclusions.

genomics↗

bioRxiv2026

An expansive animal gut microbiome dataset elucidates major compositional shifts across bilaterian evolution

Animal gut microbiomes provide key physiological functions and are critical for host health. They vary dramatically across the animal kingdom, and are shaped by factors including host diet, evolutionary history and environment. However, analyses of gut microbiomes spanning the entire metazoan clade are lacking, limiting our understanding of the fundamental principles governing gut microbiomes. Here we present the Gut Microbiome Tree of Life (GMToL), a curated 16S amplicon dataset of 17,366 samples from 1,553 host species across 26 host classes from 284 studies, enabling analysis of large-scale evolutionary trends. Using ancestral state reconstruction, we provide a critical baseline calculation of major compositional shifts in gut microbiomes throughout animal evolution. We show that the ancestral animal gut was likely dominated by Pseudomonadota. A major shift to Bacteroidota occurred during the evolution of tetrapods, followed by the emergence of Bacillota-dominated guts in mammals and birds. We identify conserved core gut microbes and demonstrate how GMToL can be leveraged to contextualize the evolutionary history of specific microbial taxa. Ultimately, this framework enables the predictive mapping of microbial symbionts across uncharacterized host lineages, and establishes a quantitative baseline for comparative microbiome research at scale.

microbiology↗

bioRxiv2026

Pan-repository analysis reveals a drug-activating function of microbial bile acid conjugation

Microbially modified bile acids shape host physiology by regulating nutrient absorption, glucose homeostasis, circadian rhythms and thermoregulation. Here we identify a previously unrecognized drug-activating function of microbial bile acid conjugation. By systematically mining human LC-MS/MS datasets across public repositories and linking uncharacterized bile acid spectra to health-associated metadata, we discovered conjugates of the >75-year-old anti-inflammatory drug 5-aminosalicylic acid (5-ASA) with primary and secondary bile acids, including cholic, deoxycholic and lithocholic acids. These bile acid-drug conjugates were detected specifically in individuals treated with 5-ASA or its prodrugs. Multiple gut bacteria, including members of the Bacteroidota and Bacillota, generated cholyl-5-ASA in vitro, and bile salt hydrolase-associated transaminase activity was required for conjugate formation. In a mouse model of colitis, cholyl-5-ASA was associated with reduced intestinal inflammatory pathology and showed markedly enhanced activation of PPAR-{gamma} in cell-based reporter assays compared with 5-ASA alone. Consistent with this activity, cholyl-5-ASA elicited selective immunophenotypic changes in CD4 T cells in vitro, including increased Foxp3+ regulatory T cells. Together with prior evidence that 5-ASA efficacy depends on the microbiome, these findings support a model in which microbial bile acid conjugation represents a key activation step for 5-ASA therapy. More broadly, this work demonstrates how pan-repository metabolomics can uncover previously unrecognized microbiome-dependent chemical functions with direct therapeutic relevance.

biochemistry↗

bioRxiv2026

Enabling Megascale Microbiome Analysis with DartUniFrac

We introduce a new algorithm, DartUniFrac, and a near-optimal implementation with GPU acceleration, up to three orders of magnitude faster than the state of the art and scaling to millions of samples (pairwise) and billions of taxa. DartUniFrac connects UniFrac with weighted Jaccard similarity and exploits sketching algorithms for fast computation. We benchmark DartUniFrac against exact UniFrac implementations, demonstrating that DartUniFrac is statistically indistinguishable from them on real-world microbiome and metagenomic datasets.

bioinformatics↗

bioRxiv2026

A searchable metadata network graph for microbiome metabolomics

Establishing the biological context of microbial metabolites remains a major challenge. We present microbiomeMASST, a metadata-driven network graph that maps metabolites across 467 available datasets with 144,424 mass spectrometry files from humans, animals, and microbial culture systems. MicrobiomeMASST integrates monocultures, synthetic communities, and host-associated samples across multiple body sites and plants. MS/MS spectra can be queried to trace occurrence across hosts, experimental conditions, and interventions, enabling cross-study integration. We demonstrate this framework by contextualizing microbial-conjugated bile acids and interrogating microbiome-mediated drug metabolism. Screening gut bacteria revealed deprolylation of the angiotensin-converting enzyme (ACE) inhibitor prodrug enalapril. Using microbiomeMASST, we traced this metabolite across human cohorts, microbial isolates, environmental samples, and in Gorilla gorilla. Structural modeling and enzymatic assays showed that microbial deprolylation abolishes ACE inhibition, thereby inactivating its therapeutic effect. Together, microbiomeMASST links MS/MS spectra to biological context, converting isolated observations into an interpretable microbiome map for cross-study analysis.

biochemistry↗

bioRxiv2025

Improved spike-in normalization clarifies the relationship between active histone modifications and transcription

Spike-in normalization enables quantitative analysis of ChIP-sequencing (ChIP-seq) signal. Here we introduce a novel robust dual-spike-in normalization approach for ChIP-seq (ChIP-wrangler). We identify optimal conditions, such as the ratio between the spike-in species and the target, demonstrate the ability of this approach to detect technical artefacts, and use ChIP-wrangler to revisit recent claims that active histone marks are dependent on transcription. Concerned that previous studies improperly used spike-in normalization to arrive at their conclusions, we used ChIP-wrangler to show that acute depletion of RNA polymerase II (RNAPII) has only a modest impact on the levels of H3K4me3 and H3K27ac. In line with other studies, our results provide proof that the maintenance of histone acetylation is not merely a consequence of ongoing transcription. Further, we show that promoters and enhancers are differentially impacted by inhibiting transcription. Specifically, of the 5.9% peaks that showed a decrease in H3K27ac following depletion of RNAPII, 82% are promoter-distal and contain enhancer-related DNA binding motifs. Further, the small subset of regions that gain acetylation (0.35%) were enriched for stress response motifs. Our innovative ChIP-seq normalization approach provides increased rigor and "guardrails" for successful spike-in normalization, and as applied here refines the understanding of the intricate crosstalk between RNAPII activity and histone marks associated with transcription.

genomics↗

bioRxiv2025

Personalised whole-body modelling links gut microbiota to metabolic perturbations in Alzheimer's disease

The human gut microbiome has been linked to metabolic disturbances in Alzheimers disease (AD). However, the mechanisms by which gut microbes might influence metabolic dysfunction in AD remain poorly understood. Previously, we used constraint-based metabolic modelling to associate an increased risk of AD with altered production of microbiome-derived metabolites. In this study, we investigated whether these previous results can also be identified in AD patients. Therefore, we created personalised whole-body metabolic models from gut metagenomics samples from 34 AD dementia patients, 51 individuals with mild cognitive impairments, and 298 healthy controls. These in silico models were profiled to predict the metabolic influences of gut microbiomes on blood metabolites with previously reported alterations in AD. We found an increased capacity of AD host-microbiome co-metabolism to produce S-adenosyl-L-methionine, L-arginine, creatine, taurine, and formate in the blood of AD dementia patients and patients with mild cognitive impairments. The metabolic predictions were then mechanistically linked to gut microbial changes in AD. This analysis identified that increased relative abundances of Bacteroides uniformis and Bacteroides thetaiotamicron were key factors driving the predicted metabolic changes. Furthermore, the predicted altered microbial influences on blood metabolites were also associated with allelic variations in the APOE risk gene in healthy individuals, which confirmed our previous findings. In conclusion, we identified blood metabolites whose perturbations in AD may be influenced by gut microbiota and predicted the key microbial drivers for these metabolic influences. These findings may facilitate the development of microbiome-informed treatments of AD.

systems biology↗

bioRxiv2025

Industrialization drives convergent microbial and physiological shifts in the human metaorganism

Understanding how host lifestyle and industrialization shape the human gut microbiome and intestinal physiology requires multimodal analyses across diverse global host contexts. Here, we generate multivariate data from the Global Microbiome Conservancy cohort, including gut microbiome, IgA-sequencing, host genotyping, diet, lifestyle and fecal biomarker profiles, to investigate host-microbiome interactions across gradients of industrialization and geography. We show that industrialization is associated with homogenized microbial compositions, reduced microbial diversity, and lower community stability, independent of host confounders. We further show that industrialization is linked to elevated markers of gut stress, increased IgA secretion, and altered patterns of IgA-bacteria interactions. Finally, we show that microbiome-based disease predictors trained on industrialized populations lose accuracy in less industrialized cohorts, highlighting limited cross-population transferability. Together, our results suggest profound restructuring of host-microbiome interactions due to industrialized lifestyles, and emphasize the need for inclusive, globally representative data to improve translational microbiome applications across diverse human populations.

microbiology↗

bioRxiv2025

spa-ChIP-seq enables the comprehensive profiling of chromatin

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map non-histone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol (Texari et al. 2021), named spa-ChIP-seq, which enables scalable processing of 8 to 96 ChIP-seq samples from crosslinked cells to sequencing-ready library in approximately three days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and crosslinking conditions, buffer compositions, and the ratio of antibody to cell-number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody to cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody-to-cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.

genomics↗

bioRxiv2025

Environmental and Maternal Imprints on Infant Gut Metabolic Programming

Early life is a critical period for immune and metabolic programming, but developmental patterns remain underexplored in populations from low- and middle-income countries. Here, we profiled the microbiome and metabolome of 55 Bangladeshi mother-infant dyads over the first six months of life. Importantly, we observed an increase in microbially-derived bile amidates and N-acyl lipids with age in conjunction with reads matching the bile salt hydrolase/transferase (bsh) gene. While microbial source tracking confirmed maternal fecal seeding, a substantial environmental contribution was also highlighted. Differences in infant fecal metabolic profiles were associated with delivery mode, maternal milk composition, household assets, and household-level water treatment. C-section delivery and untreated drinking water were linked to transient metabolic differences, including increases in bile amidates, N-acyl lipids, and other host-microbe co-metabolic products, including acylcarnitines. Multi-omics analysis revealed specific microbial-metabolite relationships, highlighting how early environmental and maternal living circumstances shape metabolic gut programming through the microbiome.

microbiology↗

bioRxiv2024

Reengineering mRNA lipid nanoparticles for systemic delivery to pancreas

Lipid nanoparticles (LNPs) hold transformative potential for nucleic acid delivery, with applications ranging from clinical use, particularly in COVID-19 vaccines, to gene therapy and cancer immunotherapy. Traditional LNPs are composed of four components: ionizable lipids, cholesterol, helper lipids, and PEGylated lipids. However, a significant hurdle remains the need for more efficient and selective systemic delivery vehicles, as most targets are challenging to reach and primarily accumulate in the liver following intravenous administration, largely due to Apolipoprotein E (ApoE) mediated uptake in the blood. Recent studies have shown that introducing cationic or anionic lipids as a fifth component in the LNPs has resulted in lung- and spleen-specific mRNA expression. In this study, we report that incorporating endogenous ligands, such as vitamins, as a fifth component can enhance the extrahepatic localization of LNPs. Vitamins are highly biocompatible, possess excellent targeting potential, influence immune response, improve cellular uptake, and increase the stability of mRNA LNPs. We developed a library of 100 LNPs containing luciferase mRNA by partially replacing ionizable lipids with this fifth component and evaluated their efficacy both in vitro and in vivo. From comprehensive batch analysis screening, we identified two formulations with cholecalciferol (vitamin D3) as a fifth component that demonstrated selective systemic delivery to the pancreas (> 99%) with high efficacy. Among these, C-CholF3 emerged as the top formulation, exhibiting robust and sustained protein expression in the pancreas for up to 3 days in a dose-dependent manner with minimal toxicity that makes it suitable for repeated administration. Furthermore, C-CholF3 also demonstrated pancreas-specific gene editing in the Ai14 transgenic mouse model, showing high expression of TdTomato. This underscores its translational potential for protein replacement and CRISPR/Cas9-mediated gene editing in currently incurable pancreatic diseases.

bioengineering↗

bioRxiv2024

Early atrial remodelling drives arrhythmia in Fabry Disease

BackgroundFabry disease (FD) is an X-linked lysosomal storage disorder caused by -galactosidase A (-Gal A) deficiency, resulting in multi-organ accumulation of sphingolipid, namely globotriaosylceramide (Gb3). This triggers ventricular myocardial hypertrophy, fibrosis, and inflammation, driving arrhythmia and sudden death, a common cause of FD mortality. Atrial fibrillation (AF) is common in FD, yet the cellular mechanisms accounting for this are unknown. To address this, we conducted electrocardiography (ECG) analysis from a large cohort of adults with FD at varying stages of cardiomyopathy. Cellular contractile and electrophysiological function were examined in an atrial FD model, developed using gene-edited atrial cardiomyocytes and imputed into in-silico atrial models to provide insight into arrhythmia mechanisms. MethodsIn 115 adults with FD, ECG P-wave characteristics were compared with non-FD controls. Induced pluripotent stem cells (iPSCs) were genome-edited using CRISPR-Cas9 to introduce the GLA p. N215S variant and differentiated into atrial cardiomyocytes (iPSC-CMs). Contraction, calcium handling and electrophysiology experiments were conducted to explore proarrhythmic mechanisms. A bi-atrial in-silico model was developed with the cellular changes induced by GLA p. N215S iPSC-CMs. ResultsECG analysis demonstrated P-wave duration and PQ interval shortening in FD adults before onset of cardiomyopathy on imaging and biochemical criteria. FD patients exhibited a higher incidence of premature atrial contractions and increased risk of developing AF. In our cellular model, GLA p. N215S iPSC-CMs were deficient in -Gal A and exhibited Gb3 accumulation. Atrial GLA p. N215S iPSC-CMs demonstrated a more positive diastolic membrane potential, faster action potential upstroke velocity, greater burden of delayed afterdepolarizations, greater contraction force, slower beat rate and dysfunction in calcium handling compared to wildtype iPSC-CMs. Inputting these changes into the in-silico model resulted in similar P-wave morphology changes to those seen in early FD cardiomyopathy and increased the action potential duration (APD) restitution slope, causing APD alternans and inducing AF. ConclusionsThese findings enhance our understanding of atrial myopathy in FD by providing novel insights into underpinning mechanisms for atrial arrhythmia and a rationale for early P-wave changes. These may be targeted in future research to develop therapeutic strategies to reduce the arrhythmic burden in FD and other atrial cardiomyopathies.

pathology↗

bioRxiv2022

Inferring pathways of oxidative folding from pre-folding free energy landscapes of disulfide-rich toxin

Short, cysteine-rich peptides can exist in stable or metastable structural ensembles due to the number of possible patterns of formation of their disulfide bonds. One interesting subset of this peptide group is the coonotoxins, which are produced by aquatic snails in the family Conidae. The {micro} conotoxins, which are antagonists and blockers of the voltage-gated sodium channel, exist in a folding spectrum: on one end of the spectrum are more hirudin-like folders, which form disulfide bonds and then reshuffle them, leading to an ensemble of kinetically trapped isomers-and on the other end are more BPTI-like folders-which form the native disulfide bonds one by one in a particular order, leading to a preponderance of conformations existing in a single stable state. In this article, we employ the composite diffusion map approach to study the unified free energy surface of pre-folding {micro}-conotoxin equilibrium. We identify the two most important nonlinear collective modes of the unified folding landscape and demonstrate that in the absence of their disulfides, the conotoxins can be thought of as largely disordered polymers. A small increase in the number of hydrophobic residues in the protein shifts the free energy landscape towards hydrophobically collapsed coil conformations responsible for cysteine proximity in hirudin-like folders, compared to semi-extended coil conformations with more distal cysteines in BPTI-like folders. Overall, this work sheds important light on the folding processes and free energy landscapes of cysteinerich peptides and demonstrates the extent to which sequence and length contribute to these landscapes.

biophysics↗

bioRxiv2019

Blinking Statistics and Molecular Counting in direct Stochastic Reconstruction Microscopy (dSTORM)

MotivationMany recent advancements in single molecule localisation microscopy exploit the stochastic photo-switching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation. ResultsModelling the photo-switching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localisations from a single photo-switching fluorophore. This is then extended to provide the probability distribution for the number of localisations in a dSTORM experiment involving an arbitrary number of molecules. We demonstrate that when training data is available to estimate photo-switching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localisations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein Linker for Activation of T cells (LAT) on the cell surface of the T cell immunological synapse. AvailabilitySoftware available at https://github.com/lp1611/mol_count_dstorm.

biophysics↗

bioRxiv2019

Structure and mechanism of a cyclic trinucleotide-activated bacterial endonuclease mediating bacteriophage immunity

Bacteria possess an array of defenses against foreign invaders, including diverse nucleases that target and destroy the genome of an invading bacteriophage or foreign DNA element. A recently-described bacteriophage immunity pathway employs a cGAS/DncV-like nucleotidyltransferase to produce a cyclic tri-AMP second messenger, which activates the DNA endonuclease effector NucC. Here, we show that NucC is related to restriction enzymes but uniquely assembles into a homotrimer in solution. cAAA binding in a conserved allosteric pocket promotes assembly of two NucC trimers into a homohexamer competent for double-strand DNA cleavage. We propose that NucC mediates bacteriophage immunity either through global activation, causing altruistic cell death and abortive infection, or through local activation and targeted phage genome destruction. Finally, we identify NucC homologs in type III CRISPR-Cas systems, where they likely function as accessory nucleases activated by cyclic oligoadenylate second messengers synthesized by these systems effector complexes.

biochemistry↗

bioRxiv2019

Mutation Of MLH3 Endonuclease Motif Reveals Integration Between Crossover Pathways In Mammalian Meiosis

During meiotic prophase I, double-strand breaks (DSBs) initiate homologous recombination leading to non-crossovers (NCOs) and crossovers (COs). In mouse, 10% of DSBs are designated to become COs, primarily through a pathway dependent on the MLH1-MLH3 heterodimer (MutL{gamma}). Mlh3 contains an endonuclease domain that is critical for resolving COs in yeast. We generated a mouse (Mlh3DN/DN) harboring a mutation within this conserved domain that is predicted to generate a protein that is catalytically inert. Mlh3DN/DN males, like fully null Mlh3-/- males, have no spermatozoa and are infertile, yet spermatocytes have normal DSBs and undergo normal synapsis events in early prophase I. Unlike Mlh3-/- males, mutation of the endonuclease domain within MLH3 permits normal loading and frequency of MutL{gamma} in pachynema. However, key DSB repair factors (RAD51) and mediators of CO pathway choice (BLM helicase) persist into pachynema in Mlh3DN/DN males, indicating a temporal delay in repair events and revealing a mechanism by which alternative DSB repair pathways may be selected. While Mlh3DN/DN spermatocytes retain only 22% of wildtype chiasmata counts, this frequency is greater than observed in Mlh3-/- males (10%), suggesting that the allele may permit partial endonuclease activity, or that other pathways can generate COs from these MutL{gamma}-defined repair intermediates in Mlh3DN/DN males. Double mutant mice homozygous for the Mlh3DN/DN and Mus81-/- mutations show losses in chiasmata that approach levels observed in Mlh3-/- males, indicating that the MUS81-EME1-regulated crossover pathway accounts for some of the increased residual chiasmata observed in Mlh3DN/DN spermatocytes. Our data demonstrate that mouse spermatocytes bearing the MLH1-MLH3DN/DN complex display the proper loading of factors essential for CO resolution (MutS{gamma}, CDK2, HEI10, MutL{gamma}). Despite these functions, mice bearing the Mlh3DN/DN allele show defects in the repair of meiotic recombination intermediates and a loss of most chiasmata. SUMMARYThe MLH1-MLH3 complex is essential for crossing over in mammalian meiosis. We generated a mutation in mouse MLH3 that alters its conserved endonuclease domain and show that it disrupts crossing over in a manner distinct from the full null Mlh3 mouse, but also results in male infertility.

genetics↗

bioRxiv2017

A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores

Fluorescing molecules (fluorophores) that stochastically switch between photon-emitting and dark states underpin some of the most celebrated advancements in super-resolution microscopy. While this stochastic behavior has been heavily exploited, full characterization of the underlying models can potentially drive forward further imaging methodologies. Under the assumption that fluorophores move between fluorescing and dark states as continuous time Markov processes, the goal is to use a sequence of images to select a model and estimate the transition rates. We use a hidden Markov model to relate the observed discrete time signal to the hidden continuous time process. With imaging involving several repeat exposures of the fluorophore, we show the observed signal depends on both the current and past states of the hidden process, producing emission probabilities that depend on the transition rate parameters to be estimated. To tackle this unusual coupling of the transition and emission probabilities, we conceive transmission (transition-emission) matrices that capture all dependencies of the model. We provide a scheme of computing these matrices and adapt the forward-backward algorithm to compute a likelihood which is readily optimized to provide rate estimates. When confronted with several model proposals, combining this procedure with the Bayesian Information Criterion provides accurate model selection.

biophysics↗