Biology subjects

Roth, A.

Publications and source records attributed to Roth, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Developmental origins of thymic B-cell lymphomas

The thymus provides a specialized niche for lymphocyte differentiation, yet the developmental trajectories of its rare B-cell population and their relationship to thymic B-cell lymphomagenesis remain poorly understood. Here, we integrate single-cell multiomics and spatial profiling across human tissues to delineate a B-cell differentiation program selectively represented in the human thymus. This program links CCL17 and germinal center-like B-cell states along a trajectory distinct from canonical germinal center differentiation and can be recapitulated in vitro by signals operating in the thymic medulla. Extending this framework across human B-cell lymphomas, we identify an inherent malignant cell state in PMBCL that shares transcriptional and epigenetic features with CCL17 thymic B cells. This malignant state associates with early clonal positions in reconstructed B-cell receptor phylogenies and persists within tumor microenvironments distinct from the thymic niche. Together, these findings support a model in which thymus-specific B-cell differentiation programs are redeployed during thymic B-cell lymphomagenesis.

cancer biology↗

bioRxiv2026

Hippocampal granule cells balance energy and function along the Pareto optimal front

The dentate gyrus' principal neuron, the granule cell (GC), plays a key role in pattern separation, transforming similar inputs into dissimilar outputs. We used a new measure based on information theory to evaluate this transformation in an experimentally derived in silico GC model with realistic ion channel distributions across its dendrites. We found that model performance aligned well with current-clamp recordings from mouse brain slices. However, it was also possible to find artificial parameter combinations in the model that functionally outperformed the recorded cells while matching their action potential shapes. Rather than maximising computational power, the biologically realistic GC model balanced energy efficiency against increased functionality in a Pareto optimal way: No possible parameter combination was found to improve one of the objectives without impairing the other. Interestingly, immature GCs adopted a different weighted trade-off with a stronger emphasis on energy efficiency than pattern separation, but they remained Pareto optimal over their putative developmental trajectory. Our results support the idea that evolution favours neurons that can satisfy functional and energetic demands simultaneously.

neuroscience↗

bioRxiv2026

Mycobacterium tuberculosis inactivates host oxysterols to impair macrophage cholesterol homeostasis

Host oxysterols coordinate macrophage cholesterol homeostasis and antimicrobial defense, but whether pathogens directly target oxysterol signaling is unknown. Here, we identify pathogen-mediated enzymatic oxysterol inactivation as a mechanism by which Mycobacterium tuberculosis (Mtb) subverts host cholesterol metabolism. Mtb oxidizes the endogenous oxysterols 27-hydroxycholesterol (27-HC) and 3{beta}-hydroxycholest-5-enoic acid (3{beta}-HCA) into 3-oxo-{Delta}4 metabolites. Sputum lipidomics across TB cohorts on three continents revealed an active-disease signature characterized by 27-HC depletion and accumulation of 27-hydroxycholest-4-en-3-one (27-HCO) and 3-oxocholest-4-enoic acid (3O-CA), which normalized with treatment. In infected human macrophages, Mtb 3{beta}-hydroxysteroid dehydrogenase (3{beta}-Hsd) generated 27-HCO. Unlike their parent oxysterols, 27-HCO and 3O-CA did not activate liver X receptor (LXR), and 3O-CA failed to suppress sterol regulatory element-binding protein 2 (SREBP2) target genes. Accordingly, 3{beta}-Hsd-deficient Mtb did not induce macrophage cholesterol retention, a phenotype restored by LXR antagonism. Thus, Mtb enzymatically inactivates host oxysterols, disrupting macrophage cholesterol homeostasis and generating treatment-responsive metabolic signatures in human TB.

microbiology↗

bioRxiv2026

Single-cell spatial multi-omic characterization of the tumour microenvironment in transformed follicular lymphoma

Histological examination of follicular lymphoma (FL) biopsies remains the cornerstone for diagnostic grading of FL. Single-cell sequencing approaches, while transcriptomically rich, require tissue dissociation and lose the native spatial context that underpins FL transformation to diffuse large B-cell lymphoma (DLBCL). To investigate the spatial interplay between malignant B-cells and the tumour microenvironment (TME) across disease states, we performed subcellular single-cell spatial transcriptomics and spatial proteomics on 12 paired pre/post-transformation samples and 10 non-transforming FL controls, integrated with matched single-cell whole genome sequencing (scWGS). Our analysis reveals that transformation is accompanied by a shift toward B-cell-predominant stromal and immunosuppressive cellular neighbourhoods, where the magnitude of expansion correlates with time to transformation. Prior to transformation, immunomodulatory Galectin-9 interactions move from the intra-follicular core to the extra-follicular space. Integration with scWGS demonstrates that high copy-number instability in malignant B-cells is associated with reduced supportive T-cell niches and intensified immunoregulatory crosstalk at the transformed state. Collectively, our multi-omic analysis characterizes TME remodeling during FL transformation, contributing to a refined disease evolution model.

bioinformatics↗

bioRxiv2025

Somatic copy number mutations contribute to fitness in transplantation models of spontaneous human breast cancer metastasis

The contribution of somatic gene dosage mutations (CNA) to breast cancer metastasis remains poorly defined. Using 9 transplantable human neoadjuvant-naive triple-negative breast cancer xenografts, we studied the fitness of copy number clones in spontaneous metastasis from orthotopic transplant sites. Metastatic site preference was strongly patient-dependent, and the emergence of metastases exhibited a general trend toward slower growth at the orthotopic site. In our models, single-cell whole-genome sequencing of primary and metastatic sites showed that distant metastases were most often the result of minor prevalence clones at the orthotopic site, suggesting that some metastatic phenotypes may be weakly negatively fit at the primary site. We validated the existence of a fitness hierarchy of copy number clones using a previously established paradigm of remixing and retransplanting clones. Single-cell clone analysis of competitive repopulation and re-emergence of metastases showed that CNAs arising in cancer evolution can mediate metastatic fitness. Moreover, some clones displaying strong metastatic tendency exhibited weaker survival at the primary site, consistent with the notion that metastatic phenotypes could have a fitness cost at the primary site. Finally, we conducted RNA-seq analysis combined with DriverNet analysis to dissect the contribution of CNA-mediated versus genome-independent transcriptional states. CNA mutations appeared to contribute strongly to transcriptional differences between clones. Among clones of high metastatic potential, we observed CNA-mediated and CNA-independent convergence on pathways such as epithelial-mesenchymal transition (EMT), established as mediators of metastatic cell survival at distant sites. Taken together, our data point to a contribution of CNA-mediated cancer evolution to metastatic states and identify distant-site context as a key determinant of CNA-mediated fitness.

cancer biology↗

bioRxiv2025

A Physically-Realistic Simulator and Cosine-Based Decoder for MERFISH Spatial Transcriptomics

Imaging-based spatial transcriptomics technologies have opened new avenues for studying cellular organization and gene expression within intact tissues. However, the accuracy of downstream analyses depends critically on the decoding step that reconstructs barcodes from fluorescence patterns and maps them to gene identities. Despite a growing number of decoding methods, systematic benchmarking has been limited. Here, we introduce Serval, a modular framework for developing and benchmarking decoding methods across diverse spatial transcriptomics platforms. Serval separates key decoding stages into independently configurable modules, enabling flexible integration of alternative algorithms. Using this framework, we develop the Cosine decoder, a novel method that improves transcript recovery by optimizing cosine similarity to known barcodes. We evaluate Cosine and baseline methods on synthetic and real MERFISH datasets, showing that Cosine achieves higher transcript recovery and superior correlation with expression references compared to existing methods. Furthermore, we demonstrate that the Serval framework generalizes beyond MERFISH. By extending to the DART-FISH platform, we show that Cosine improves transcript recovery, clustering stability and supports more direct annotation of complex biological structures such as the human primary motor cortex. These results establish that modular decoding frameworks facilitate robust, platformagnostic benchmarking, ultimately supporting more accurate spatial transcriptomics analysis across diverse biological samples.

bioinformatics↗

bioRxiv2025

An orally available PfPKG inhibitor blocks sporozoite infection of the liver

Malaria remains a global health threat exacerbated by emerging resistance to antimalarial therapies and insecticides, climate-driven outbreaks, and limited chemoprotective options. Here, we report the characterization of RUPB-61, the first orally bioavailable inhibitor of Plasmodium falciparum cGMP-dependent protein kinase (PfPKG). RUPB-61 prevents infection by P. falciparum and P. cynomolgi sporozoites, including the formation of hypnozoites by the latter. A single oral dose blocks liver infection by P. berghei sporozoites in vivo, demonstrating efficacy consistent with further development as a once-weekly prophylaxis based on pharmacokinetic modeling. The compound retains activity against field isolates resistant to chloroquine, mefloquine, cycloguanil, sulfadoxine and pyrimethamine, suggesting low likelihood of cross-resistance to existing antimalarials. Structural studies and free energy-based modeling guided-compound design prospectively validated the predictive accuracy of an in silico model of PfPKG interactions with this chemotype. While selectivity profiling identified off-target activity against human kinases, structural modeling provides a clear path for optimization. These results establish PfPKG inhibitors as promising candidates for chemoprevention and support further preclinical development of the RUPB-61 chemotype. Author SummaryMalaria remains a serious global health threat, made worse by growing resistance to existing drugs and the spread of insecticide-resistant mosquitoes. A critical gap in our prevention toolkit is the lack of safe, long-acting oral drugs that stop malaria parasites from infecting the liver - the first and obligatory step of every new infection. Here, we report the characterization of RUPB-61, a compound that blocks an enzyme that the malaria parasite needs to invade and survive in the liver. We show that a single oral dose completely prevents liver infection in mice, and that the compound remains active against parasites that are resistant to several currently used antimalarial drugs. Using X-ray crystallography and computer-based modeling, we determined how RUPB-61 binds to its target in atomic detail, providing a roadmap for designing improved versions. While the compound shows some unwanted interactions with human proteins, our structural data offer clear strategies to solve this challenge. Together, these findings provide a solid foundation for developing a new class of once-weekly oral malaria prevention drugs.

microbiology↗

bioRxiv2025

Antibiotics-induced conformational heterogeneity of a multidrug transporter revealed by single-molecule FRET

Multidrug transporters are membrane proteins that can transport an ensemble of structurally dissimilar compounds and contribute to bacterial multidrug resistance (MDR) by exporting different antibiotics from the cell. However, whether they transport different substrates through a common mechanism or via distinct substrate-dependent mechanisms remains unclear. In this work, we used single-molecule Forster resonance energy transfer (smFRET) to measure time-resolved conformational dynamics of LmrP, a multidrug transporter of the Major Facilitator Superfamily (MFS). We present high-resolution conformational landscapes of LmrP in the presence of different antibiotics. Through multi-parameter Hidden Markov Modeling (mpH2MM), we uncovered transient states and quantified their sub-millisecond interconversion kinetics. We observed antibiotic-dependent heterogeneity in the conformational landscape, both in accessible states and in interconversion rates. Notably, poorly or non-transported antibiotics slow down transition kinetics, pointing to rapid state interconversion as a driver of efficient transport. This suggests that MFS MDR transporters bind and export structurally dissimilar antibiotics by relying on an array of underlying conformational states with ligand-dictated interconversion rates. This work provides novel insights into the mechanism of MDR transporters and advocates for combined structure/dynamics-based drug design when targeting their function.

biophysics↗

bioRxiv2025

Single particle dynamics of protein aggregation and disaggregation in the presence of the sHsp proteins IbpAB

The small heat shock proteins (sHsps) are a key class of molecular chaperones that can inhibit protein aggregation and enhance protein recovery from aggregates. However, the mechanisms sHsps employ to carry out these roles are not well understood, in part because the highly heterogeneous and dynamic particles they form with aggregating proteins are difficult to study with traditional biophysical tools. Here we have applied a novel single particle fluorescence technique known as Burst Analysis Spectroscopy (BAS) to the study of the E. coli sHsps IbpA and IbpB (IbpAB). We show that in the presence of IbpAB, two different model proteins converge toward similar, limited aggregate particle size distributions. Additionally, while IbpAB dramatically accelerates the disassembly of protein aggregates by the bacterial KJEB bi-chaperone disaggregase, this enhancement does not appear to be strongly influenced by aggregate particle size. Rather, it is the ability of IbpAB to alter aggregate structure during particle formation that appears to be essential for stimulated disassembly. These observations support a model of aggregate recognition by IbpAB that is not only highly adaptable but capable of shaping aggregate particles into a specialized range of physical properties that are necessary for efficient protein disaggregation.

biochemistry↗

bioRxiv2025

Multidimensional characterization of cellular ecosystems in Hodgkin lymphoma

The tissue architecture of classic Hodgkin Lymphoma (CHL) is unique among cancers and characterized by rare malignant Hodgkin and Reed-Sternberg cells that co-evolve with a complex ecosystem of immune cells in the tumor microenvironment (TME). The lack of a comprehensive systems-level interrogation has hindered the description of disease heterogeneity and clinically relevant molecular subtypes. Here, we employed an integrative, multimodal approach to characterize CHL tumors using malignant cell sequencing, spatial transcriptomics and imaging mass cytometry. We identified four molecular subtypes (CST, CN913, STB, and CN2P), each characterized by distinct clinical features, mutational patterns, malignant cell gene expression profiles, and spatial architecture involving immune cell populations. Functional modeling of CSF2RB mutations, a characteristic feature of the CST subtype, revealed dysregulated oncogenic signaling and unique TME crosstalk. These findings highlight the significance of multi-dimensional profiling in elucidating patterns of molecular alterations that drive immune ecosystems and underlie therapeutically exploitable vulnerabilities.

cancer biology↗

bioRxiv2024

PhyClone: Accurate Bayesian reconstruction of cancer phylogenies from bulk sequencing

MotivationCancer is driven by somatic mutations that result in the expansion of genomically distinct sub-populations of cells called clones. Identifying the clonal composition of tumours and understanding the evolutionary relationships between clones is a crucial task in cancer genomics. Bulk DNA sequencing is commonly used for studying the clonal composition of tumours, but it is challenging to infer the genetic relationship between different clones due to the mixture of different cell populations. ResultsIn this work, we introduce a new probabilistic model called PhyClone that can infer clonal phylogenies from bulk sequencing data. We demonstrate the performance of PhyClone on simulated and real-world datasets and show that it outperforms previous methods in terms of accuracy and scalability. Availability and implementationSource code is available on Github at: https://github.com/Roth-Lab/PhyClone under the GPL v3.0 license. Contactaroth@bccrc.ca

bioinformatics↗

bioRxiv2024

A latent pool of neurons silenced by sensory-evoked inhibition can be recruited to enhance perception

Which patterns of neural activity in sensory cortex are relevant for perceptual decision-making? To address this question, we used simultaneous two-photon calcium imaging and targeted two-photon optogenetics to probe barrel cortex activity during a perceptual discrimination task. Head-fixed mice discriminated bilateral whisker deflections and reported decisions by licking left or right. Two-photon calcium imaging revealed sparse coding of contralateral and ipsilateral whisker input in layer 2/3 while most neurons did not show task-related activity. Activating small groups of pyramidal neurons using two-photon holographic photostimulation evoked a perceptual bias that scaled with the number of neurons photostimulated. This effect was dominated by the optogenetic activation of a small number of non-coding neurons, which did not show sensory or motor-related activity during task performance. Patterned photostimulation also revealed potent recruitment of cortical inhibition during sensory processing, which strongly and preferentially suppressed non-coding neurons. Our results provide a novel perspective on the circuit basis for the sparse coding model of somatosensory processing in which a pool of non-coding neurons, selectively suppressed by strong network inhibition during whisker stimulation, can be recruited to enhance perception. HighlightsO_LIAll-optical interrogation of barrel cortex during bilateral whisker discrimination C_LIO_LISparse coding of contralateral and ipsilateral whisker information C_LIO_LISelective sensory-evoked inhibition helps ensure sparse coding C_LIO_LIOptogenetic recruitment of stimulus non-coding neurons can aid perception C_LI

neuroscience↗

bioRxiv2023

Single cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BackgroundThe encoding of cell intrinsic resistance states in breast cancer reflects the contributions of genomic and non-genomic variation. However, identifying the potential contributions of each requires accurate measurement and subtraction of the contribution of clonal fitness from co-measurement of transcriptional states. Somatic genomic variation in gene dosage, copy number variation, is the dominant mutational mechanism in breast cancer contributing to transcriptional variation and has recently been shown to contribute to platinum chemotherapy resistance states. Here we deploy time series measurements of triple negative breast cancer single cell transcriptomes in conjunction with co-measured single cell copy number associated clonal fitness to identify the contributions of genomic and non-genomic mechanisms to drug associated transcription states. ResultsWe generated serial scRNA-seq data (126,556 cells) from triple negative breast cancer (TNBC) patient-derived xenograft (PDX) experiments over 2.5 years in duration, and matched it against genomic copy number single cell data from the same biological samples. We show that the cell memory of transcriptional states of TNBC tumors serially exposed to platinum identifies distinct clonal responses within individual tumours. Copy-number clones with high drug fitness leading to clonal sweeps exhibit less transcriptional reversion, whereas clones with weak drug fitness exhibit highly dynamic transcription on drug withdrawal. Pathway analysis shows that copy number associated and copy number independent transcripts converge on epithelial-mesenchymal transition (EMT) and cytokine signaling states associated with resistance. We show from trajectory analysis that transcriptional reversion exhibits hysteresis, indicating that new intermediate transcriptional states are generated by platinum exposure. ConclusionsWe discovered that copy number clones with strong genotype associated fitness under platinum became fixed in their states, resulting in minimal transcriptional reversion on drug withdrawal. In contrast clones with weaker fitness undergo non-genomic transcriptional plasticity and these distinct responses co-exist within single tumours. Together the data suggest that copy number associated and copy number independent transcriptional states may contribute to platinum drug resistance within individual tumours. The dominance of genomic or non-genomic mechanisms within individual polyclonal tumours has implications for approaches to restoration of drug sensitivity and re-treatment strategies. Data availabilityUploaded Data URL: https://ega-archive.org/studies/EGAS00001007242 Github manuscript: https://github.com/molonc/drug_resistant_material/

genomics↗

bioRxiv2023

ESQmodel: biologically informed evaluation of 2-D cell segmentation quality in multiplexed tissue images

MotivationSingle cell segmentation is critical in the processing of spatial omics data to accurately perform cell type identification and analyze spatial expression patterns. Segmentation methods often rely on semi-supervised annotation or labeled training data which are highly dependent on user expertise. To ensure the quality of segmentation, current evaluation strategies quantify accuracy by assessing cellular masks or through iterative inspection by pathologists. While these strategies each address either the statistical or biological aspects of segmentation, there lacks an unified approach to evaluating segmentation accuracy. ResultsIn this paper, we present ESQmodel, a Bayesian probabilistic method to evaluate single cell segmentation using expression data. By using the extracted cellular data from segmentation and a prior belief of cellular composition as input, ESQmodel computes per cell entropy to assess segmentation quality by how consistent cellular expression profiles match with cell type expectations. Availability and implementationSource code is available on Github at: https://github.com/Roth-Lab/ESQmodel under the MIT license.

bioinformatics↗

bioRxiv2023

The spatially resolved tumor microenvironment predicts treatment outcome in relapsed/refractory Hodgkin lymphoma

PURPOSEAbout a third of relapsed or refractory classic Hodgkin lymphoma (r/r CHL) patients succumb to their disease after high-dose chemotherapy followed by autologous stem cell transplantation (HDC/ASCT). Here, we aimed to describe spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL. METHODSWe performed imaging mass cytometry (IMC) on 169 paired primary diagnostic and relapse biopsies using a marker panel specific for CHL biology. For each cell type in the TME, we calculated a spatial score measuring the distance of nearest neighbor cells to the malignant Hodgkin Reed Sternberg cells within close interaction range. Spatial scores were used as features in prognostic model development for post-ASCT outcomes. RESULTSHighly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early relapse/refractory CHL samples, whereas TME patterns were more divergent in pairs of diagnostic and late relapse samples. Integrated analysis of IMC and single cell RNA sequencing data identified unique architecture defined by CXCR5+ HRS cells and their strong spatial relationship with CXCL13+ macrophages in the TME. We developed a prognostic assay ( RHL4S) using four spatially resolved parameters, CXCR5+ HRS cells, PD1+CD4+ T cells, tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk vs low-risk groups with significantly different post-ASCT outcomes. The RHL4S assay was validated in an independent r/r CHL cohort using a multicolor immunofluorescence assay. CONCLUSIONSWe identified the interaction of CXCR5+ HRS cells with ligand-expressing CXCL13+ macrophages as a prominent crosstalk axis in relapsed CHL. Harnessing this TME biology, we developed a novel prognostic model applicable to r/r CHL biopsies, RHL4S, opening new avenues for spatial biomarker development.

cancer biology↗

bioRxiv2023

The dominance of coinfecting parasites' indirect effects on host traits

Indirect genetic effects (IGEs) exist when there is heritable variation in one species ability to alter a second species traits. For example, parasites can evolve disparate strategies to manipulate host immune response, whether by evading detection or suppressing immunity. A complication arises during coinfection, when two or more parasite genotypes may try to impose distinct IGEs on the same host trait: which parasites IGE will be dominant? Here, we apply the notion of dominance to IGEs during coinfection. Using a mathematical model we show that the dominance of IGEs can alter the evolutionary dynamics of parasites. We consider a resident parasite population receiving rare immigrants with a different immune manipulation trait. These immigrants relative fitness depends on resident prevalence (e.g., the probability immigrants are alone in a host, or coinfecting with a native), and the dominance of the immigrants IGE on host immunity. Next, we show experimentally that the cestode Schistocephalus solidus exerts an IGE on a host immune trait: parasite antigens from different populations produced different intensities of fibrosis. We then evaluated IGE dominance, finding evidence for overdominance (coinjected antigens induced an even stronger host immune response) which would be detrimental to immigrants when resident prevalence is high. This combination of experimental and modeling results shows that parasites do exhibit IGEs on host traits, and that the dominance of these IGEs during coinfection can substantially alter parasite evolution.

evolutionary biology↗

bioRxiv2022

Development of an Ectopic huLiver Model for Plasmodium Liver Stage Infection

Early Plasmodium falciparum and P. vivax infection requires parasite replication within host hepatocytes, referred to as liver stage (LS). However, limited understanding of infection dynamics in human LS exists due to species-specificity challenges. Reported here is a reproducible, easy-to-manipulate, and moderate-cost in vivo model to study human Plasmodium LS in mice; the ectopic huLiver model. Ectopic huLiver tumors were generated through subcutaneous injection of the HC-04 cell line and shown to be infectible by both freshly dissected sporozoites and through the bite of infected mosquitoes. Evidence for complete LS development was supported by the transition to blood-stage infection in mice engrafted with human erythrocytes. Additionally, this model was successfully evaluated for its utility in testing antimalarial therapeutics, as supported by primaquine acting as a causal prophylactic against P. falciparum. Presented here is a new platform for the study of human Plasmodium infection with the potential to aid in drug discovery.

molecular biology↗

bioRxiv2022

Integrated single cell analysis reveals co-evolution of malignant B cells and the tumor microenvironment in transformed follicular lymphoma

Follicular lymphoma (FL) is the most common indolent form of non-Hodgkin lymphoma. Histological transformation of FL to a more aggressive form of lymphoma occurs with a linear incidence of 2-3% per year and is associated with poor outcome. Divergent clonal evolution and an altered tumour microenvironment (TME) have both been implicated in the transformation process. However, the phenotypic consequences of this evolution and its implication in reshaping the TME remain unknown. To address this knowledge gap we performed single cell whole genome (scWGS) and single cell whole transcriptome sequencing (scWTS) of paired pre/post transformation samples of 11 FL patients. We further performed scWTS analysis of additional 11 FL samples from patients that had not undergone transformation within 7 years. Our comprehensive single cell analysis revealed the evolutionary dynamics of transformation at unprecedented resolution. Computational integration of scWGS and scWTS allowed us to identify gene programs upregulated and positively selected during evolution. Furthermore, our scWTS analysis revealed a shifting TME landscape, with an exhausted CD8 T cell signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a novel TME based biomarker of transformation, subsequently validated in 2 independent cohorts of pretreatment FL samples. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and the shifting cross-talk between malignant cells and the TME. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/516951v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@92abf7org.highwire.dtl.DTLVardef@157f2c2org.highwire.dtl.DTLVardef@102a879org.highwire.dtl.DTLVardef@182daec_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗