Biology subjects

Singh, R.

Publications and source records attributed to Singh, R..

At least 181 records · Page 10Linked to original sources

bioRxiv2022

Contrasting drugs from decoys

Protein language models (PLMs) have recently been proposed to advance drugtarget interaction (DTI) prediction, and have shown state-of-the-art performance on several standard benchmarks. However, a remaining challenge for all DTI prediction models (including PLM-based ones) is distinguishing true drugs from highly-similar decoys. Leveraging techniques from self-supervised contrastive learning, we introduce a second-generation PLM-based DTI model trained on triplets of proteins, drugs, and decoys (small drug-like molecules that do not bind to the protein). We show that our approach, CON-Plex, improves specificity while maintaining high prediction accuracy and generalizability to new drug classes. CON-Plex maps proteins and drugs to a shared latent space which can be interpreted to identify mutually-compatible classes of proteins and drugs. Data and code are available at https://zenodo.org/record/7127229.

bioinformatics↗

bioRxiv2022

ALaSCA: a computational platform for quantifying the effect of proteins using Pearlian causal inference, with an example application in Alzheimer's disease

IntroductionAn urgent need to delay the onset of aging-associated diseases has arisen due to increasing human lifespan. A dramatic surge in the number of identified potential molecular targets that could promote successful aging, has led to the challenge of prioritizing these targets for further research and drug development. In our previous work, we prioritized genes associated with aging processes based on their similarity to known aging-related genes and dysfunction marker genes in C. elegans. The goal of this study was to demonstrate the ability of our computational platform to identify molecular drivers of neuronal aging using specialized causal inference techniques. S6K was highly ranked in the previous study and here the nearby neighbors in its protein interaction network were selected to explore ALaSCAs (Adaptable Large-Scale Causal Analysis) ability to identify possible drivers of Alzheimers disease. MethodsUtilizing head and brain proteome data, two of ALaSCAs capabilities were used to understand how protein changes over the lifespan of Drosophila melanogaster affect a feature of neuronal aging, namely climbing ability: O_LIPearson correlation analysis was used to assess the relationship between the changes in abundance of specific proteins associated (through protein-protein interactions) with S6K and climbing ability. C_LIO_LIPearlian causal inference, required to achieve formal causal analysis, was used to determine which pathway, associated with proteins linked to S6K, has the largest effect on climbing ability and therefore to what degree these specific proteins are driving neuronal aging. C_LI Results and discussionBased on the correlation results, the proteins associated with fz, a gene encoding for the fz family of receptors that are involved in Wnt signaling, display an increase in abundance as climbing ability declines over time. When viewed together with the fz proteins strong negative causal value, it seems that their increased abundance over the lifespan of Drosophila is an important driver of the observed decrease in climbing ability. Additionally, expression of the genes FZD1 and FZD7 (fz orthologs) is altered in the hippocampus early on in Alzheimers disease human samples and in an amyloid precursor protein mouse model. ConclusionWe have demonstrated the potential of the ALaSCA platform to identify and provide evidence behind molecular mechanisms. This capability enables identification of possible drivers of Alzheimers disease - as the human orthologs of the proteins identified here, through its Pearlian causal inference capability, have been linked to Alzheimers disease progression.

bioinformatics↗

bioRxiv2022

Unraveling causal gene regulation from the RNA velocity graph using Velorama

Single-cell expression dynamics from differentiation trajectories or RNA velocity have the potential to reveal causal links between transcription factors (TFs) and their target genes in gene regulatory networks (GRNs). However, existing methods either neglect these expression dynamics or require cells to be ordered along a linear pseudotemporal axis, which is incompatible with branching trajectories. We introduce Velorama, an approach to causal GRN inference that represents single-cell differentiation dynamics as a directed acyclic graph (DAG) of cells constructed from pseudotime or RNA velocity measurements. In contrast to previous approaches, Velorama is able to work directly with RNA velocity-based cell-to-cell transition probabilities and enables estimates of TF interaction speeds with their target genes. On a set of synthetic datasets, Velorama substantially outperforms existing approaches, improving area under the precision-recall curve (AUPRC) by 3.7-4.8x over the next best method. Applying Velorama to four RNA velocity datasets, we uncover evidence that the speed of a TFs interactions is tied to its regulatory function. For human corticogenesis, we find slow TFs to be linked to gliomas and co-regulate preferentially with fast TFs, while fast TFs are associated with neuropsychiatric diseases. We expect Velorama to be a critical part of the RNA velocity toolkit for investigating the causal drivers of differentiation and disease. Software availabilityhttps://cb.csail.mit.edu/cb/velorama

bioinformatics↗

bioRxiv2022

GrapHiC: An integrative graph based approach for imputing missing Hi-C reads

Hi-C experiments allow researchers to study and understand the 3D genome organization and its regulatory function. Unfortunately, sequencing costs and technical constraints severely restrict access to high-quality Hi-C data for many cell types. Existing frameworks rely on a sparse Hi-C dataset or cheaper-to-acquire ChIP-seq data to predict Hi-C contact maps with high read coverage. However, these methods fail to generalize to sparse or cross-cell-type inputs because they do not account for the contributions of epigenomic features or the impact of the structural neighborhood in predicting Hi-C reads. We propose GrapHiC, which combines Hi-C and ChIP-seq in a graph representation, allowing more accurate embedding of structural and epigenomic features. Each node represents a binned genomic region, and we assign edge weights using the observed Hi-C reads. Additionally, we embed ChIP-seq and relative positional information as node attributes, allowing our representation to capture structural neighborhoods and the contributions of proteins and their modifications for predicting Hi-C reads. Our evaluations show that GrapHiC generalizes better than the current state-of-the-art on cross-cell-type settings and sparse Hi-C inputs. Moreover, we can utilize our framework to impute Hi-C reads even when no Hi-C contact map is available, thus making high-quality Hi-C data more accessible for many cell types. Availabilityhttps://github.com/rsinghlab/GrapHiC ACM Reference FormatGhulam Murtaza, Justin Wagner, Justin M. Zook, and Ritambhara Singh. 2018. GrapHiC: An integrative graph based approach for imputing missing Hi-C reads. In Proceedings of 22nd International Workshop on Data Mining in Bioinformatics (BioKDD 23). ACM, New York, NY, USA, 16 pages. https://doi.org/XXXXXXX.XXXXXXX

genomics↗

bioRxiv2022

A novel porcine model of CLN3 Batten disease recapitulates clinical phenotypes

Mouse models of CLN3 Batten disease, a rare lysosomal storage disorder with no cure, have improved our understanding of CLN3 biology and therapeutics through their ease of use and a consistent display of cellular pathology. However, the translatability of murine models is limited by disparities in anatomy, body size, life span, and inconsistent, subtle behavior deficits that can be difficult to detect in CLN3 mutant mouse models, limiting their utility in preclinical studies. Here we present a longitudinal characterization of a novel miniswine model of CLN3 disease that recapitulates the most common human pathogenic variant, an exon 7-8 deletion (CLN3{Delta}ex7/8). Progressive pathology and neuron loss is observed in various regions of the CLN3{Delta}ex7/8 miniswine brain and retina. Additionally, mutant miniswine present with vision impairment and motor abnormalities, similar to deficits seen in human patients. Taken together, the CLN3{Delta}ex7/8 miniswine model shows consistent and progressive Batten disease pathology and behavioral impairment mirroring clinical presentation, demonstrating its value in studying the role of CLN3 and safety/efficacy of novel disease modifying therapeutics.

neuroscience↗

bioRxiv2022

Subcutaneous BCG vaccination protects against streptococcal pneumonia via regulating innate immune responses in the lung

Bacillus Calmette-Guerin (BCG) still remains the only licensed vaccine for TB and has been shown to provide nonspecific protection against unrelated pathogens. This has been attributed to the ability of BCG to modulate the innate immune system, known as trained innate immunity (TII). TII is associated with innate immune cells being in a hyper-responsive state leading to enhanced host defense against heterologous infections. Both epidemiological evidence and prospective studies demonstrate cutaneous BCG vaccine-induced TII provides enhanced innate protection against heterologous pathogens. Regardless of the extensive amounts of progress made thus far, the effect of cutaneous BCG vaccination against heterologous respiratory bacterial infections and the underlying mechanisms remain unknown. Here we show for the first time that s.c BCG vaccine-induced TII provides enhanced heterologous innate protection against pulmonary S. pneumoniae infection. We further demonstrate that this enhanced innate protection is mediated by accelerated neutrophilia in the lung and is independent of centrally trained circulating monocytes. New insight from this study will help design novel effective vaccination strategies against unrelated respiratory bacterial pathogens.

immunology↗

bioRxiv2022

An IBD-associated pathobiont synergises with NSAID to promote colitis which is blocked by NLRP3 inflammasome and Caspase-8 inhibitors

Conflicting evidence exists on the association between consumption of non-steroidal anti-inflammatory drugs (NSAIDs) and symptomatic worsening of inflammatory bowel disease (IBD). We hypothesise that the heterogeneous prevalence of pathobionts [e.g., adherent-invasive Escherichia coli (AIEC)], might explain this inconsistent NSAIDs/IBD correlation. Using IL10 -/- mice, we show aggravation of colitis in AIEC-colonised animals fed NSAID. This is accompanied by activation of the NLRP3 inflammasome, Caspase-8, apoptosis and pyroptosis; features not seen in mice exposed to AIEC or NSAID alone, revealing an AIEC/NSAID synergistic effect. Inhibition of NLRP3 or Caspase-8 activity ameliorated colitis, with reduction in NLRP3 inflammasome activation, cell death markers and activated T-cells and macrophages, improved histology and increased abundance of Clostridium cluster XIVa species. Our findings provide mechanistic insights into how NSAID and an opportunistic gut-pathobiont can synergise to worsen IBD symptoms. Thus, targeting the NLRP3 inflammasome and Caspase-8 could be a potential therapeutic strategy in patients with NSAID-worsened inflammation.

immunology↗

bioRxiv2022

Resistance screening and in-silico characterization of cloned novel RGA from multi race resistant Lentil germplasm against Fusarium wilt (Fusarium oxysporum f. sp. lentis)

Fusarium wilt caused by Fusarium oxysporum f. sp. lentis (Fol) is the most devastating disease of lentil present worldwide and in India. Identification of multi-race fusarium wilt resistance genes and incorporation into existing cultivar will help to reduce yield loss. In the present study, a hundred lentil germplasm were screened against seven prevalent races of Fol and accession IC201561, EC714243 and EC718238 were identified resistant. The typical R gene codes for the nucleotide-binding site and leucine-rich repeats (NBS-LRR) at the C terminal linked to either Toll/interleukin 1-like receptor (TIR) or coiled-coil (CC) at the N terminal. In the present study degenerate primers designed from the NBS region amplifying P-loop to GLPLA motif isolated forty-five resistance gene analogues (RGA) from identified resistant accessions. The sequence alignment identified both classes of RGA, TIR and non-TIR based on the presence of Aspartate (D) and Tryptophan (W) at the end of kinase motif respectively. The phylogenetic analysis grouped RGA into six classes, LRGA1 to LRGA6 determining the diversity of RGA present in the host. Grouping of RGA identified from Lens nigricans, LnRGA 2, 9, 13 with I2 reveals a probable role in Fusarium resistance. The similarity index of 27.85% to 86.98% was found among RGA and 26.83% to 49.41% between known R genes, I2, Gpa2, M and L6. Active binding sites present along the conserved motifs have grouped the RGA into 13 groups. ADP/ATP being the potential ligand determines ATP binding and ATP hydrolysis activity of RGA. The isolated RGA can be used in developing marker linked to the functional R gene. Further, expression analysis and full-length gene isolation further pave path to identifying the molecular mechanism involved in resistance.

pathology↗

bioRxiv2022

Comparative analysis of drug-salt-polymer interactions by experiment and molecular simulation improves biopharmaceutical performance

The propensity of poorly water-soluble drugs to aggregate at supersaturation impedes their bioavailability. The emergence of supersaturated amorphous drug-salt-polymer systems provides a new approach to this problem. However, the effects of polymers on drug-drug interactions in aqueous phase are largely unexplored and it is unclear how to choose an optimal salt-polymer combination for a particular drug. We describe a comparative experimental and computational characterization of amorphous solid dispersions containing the drug celecoxib, and PVP-VA or HPMCAS polymers with or without Na+/K+ salts. Classical models for drug-polymer interactions fail to identify the best drug-salt-polymer combination. In contrast, more stable drug-polymer interaction energies computed from molecular dynamics simulations correlate with prolonged stability of supersaturated amorphous drug-salt-polymer systems, along with better dissolution and pharmacokinetic profiles. The celecoxib-salt-PVP-VA formulations exhibit excellent biopharmaceutical performance, offering the prospect of less frequent administration and lower doses of this widely used anti-inflammatory, thereby increasing cost-effectiveness, and reducing side-effects.

pharmacology and toxicology↗

bioRxiv2022

Exploring oxidative stress and endothelial dysfunction as a mechanism linking bisphenol S exposure to vascular disease in human umbilical vein endothelial cells and a mouse model of postnatal exposure.

BackgroundStructural analogues used to replace bisphenol A (BPA) since the introduction of new regulatory restrictions are considered emerging environmental toxicants and remain understudied with respect to their biological actions and health effects. Studies reveal a link between BPA exposure and vascular disease in human populations, whereas the vascular effects of BPA substitutes remain largely unknown. ObjectivesTo determine the effect of BPS, a commonly used BPA substitute, on redox balance, nitric oxide (NO) availability and microvascular NO-dependent dilation. MethodsIn human umbilical vein endothelial cells (HUVEC), production of reactive oxygen species (ROS) and NO after exposure to BPS was measured using fluorescent probes for DCFDA and DAF-FM diacetate, respectively. The contribution of endothelial NO synthase (eNOS) uncoupling to ROS generation was determined by measuring ROS in the presence or absence of an eNOS inhibitor (L-NAME) or eNOS co-factor, BH4, while the contribution of mitochondria-derived ROS was determined by treating cells with mitochondria-specific antioxidants prior to BPS exposure. Bioenergetic profiles were assessed using Seahorse extracellular flux analysis and mitochondria membrane polarization was measured with TMRE and JC-1 assays. In a mouse model of low dose BPS exposure, NO-mediated endothelial function was assessed in pressurized microvessels by inducing endothelium-dependent dilation in the presence or absence of L-NAME. ResultsBPS exposure ([≥] 25 nM) reduced NO and increased ROS production in HUVEC, the latter corrected by treating cells with L-NAME or BH4. BPS exposure led to a loss of mitochondria membrane potential but had no impact on bioenergetic parameters except for a decrease in the spare respiratory capacity. Treatment of HUVEC with mitochondria-specific antioxidants abolished the effect of BPS on NO and ROS. NO-mediated vasodilation was impaired in male mice exposed to BPS. DiscussionExposure to BPS may promote cardiovascular disease by perturbing NO-mediated vascular homeostasis through the induction of oxidative stress.

physiology↗

bioRxiv2022

Structural Mechanisms of Actin Isoforms

Actin isoforms organize into distinct networks that are essential for the normal function of eukaryotic cells. Despite a high level of sequence and structure conservation, subtle changes in their design principles determine the interaction with myosin motors and actin-binding proteins. The functional diversity is further increased by posttranslational modifications (PTMs). Therefore, identifying how the structure of actin isoforms relates to function is important for our understanding of normal cytoskeletal physiology. Here, we report the high-resolution structures of filamentous skeletal -actin (3.37[A]), cardiac -actin (3.07[A]), {beta}-actin (2.99[A]), and {gamma}-actin (3.38[A]) in the Mg2+{middle dot}ADP state with their native PTMs. The structures revealed isoform-specific conformations of the N-terminus that shifts closer to the filament surface upon myosin binding, thereby establishing isoform-specific interfaces. Retropropagated structural changes further show that myosin binding modulates actin filament structure. Further, our structures enabled us to reveal the location of disease-causing mutations and to analyze them with respect to known locations of PTMs. Collectively, the previously unknown structures of single-isotype, posttranslationally modified bare cardiac -actin, {beta}-actin, and {gamma}-actin reveal general principles, similarities, and differences between isoforms. They complement the repertoire of known actin structures and allow for a comprehensive understanding of in vitro and in vivo functions of actin isoforms.

biochemistry↗

bioRxiv2022

Acinetobacter baumannii defends against oxidative stress through a Mn2+-dependent small RNA-mediated suppression of type VI secretion system

Type VI secretion system (T6SS) is utilized by many Gram negative bacteria for eliminating competing bacterial species and manipulating host cells. Acinetobacter baumannii ATCC 17978 utilizes T6SS at the expense of losing pAB3 plasmid to induce contact-dependent killing of competitor microbes, resulting in the loss of antibiotic resistance carried by pAB3. However, the regulatory network associated with T6SS in A. baumannii remains poorly understood. Here, we identified an Mn2+-dependent post-transcriptional regulation of T6SS mediated by a bonafide small RNA, AbsR28. A. baumannii utilizes MumT (Mn2+-uptake inner membrane transporter) for the uptake of extracellular Mn2+ during oxidative stress. We demonstrate that the abundance of intracellular Mn2+ enables complementary base-pairing of AbsR28-tssM mRNA (that translated to TssM, one of the vital inner membrane components of T6SS), inducing RNase E-mediated degradation of tssM mRNA and resulting in T6SS repression. Thus, AbsR28 mediates a crosstalk between MumT and T6SS in A. baumannii. IMPORTANCESmall RNAs (sRNAs) are identified as critical components within the bacterial regulatory networks involved in fine regulation of virulence-associated factors. The sRNA-mediated regulation of Acinetobacter baumanniis T6SS was unchartered. Our findings reveal a novel underlying mechanism of an Mn2+-dependent sRNA-mediated regulation of T6SS in A. baumannii. We show that binding of Mn2+ to AbsR28 aids in the complementary base-pairing of AbsR28-tssM mRNA, resulting in RNase E-mediated processing of tssM and T6SS repression. The findings also shed light on A. baumanniis preference for antibiotic resistance over contact-dependent killing during infection.

microbiology↗

bioRxiv2022

mTORC2 couples fasting to mitochondrial fission

Fasting triggers diverse cellular and metabolic adaptations to facilitate organismal survival1,2. During nutrient deprivation, increases in circulating fatty acids support mitochondrial respiration2. The mechanisms driving mitochondrial adaptations and respiratory sufficiency during nutrient deprivation remain incompletely understood. Here we show that extended periods of fasting, or lipid availability stimulates mTORC2 activity. Activation of mTORC2 and phosphorylation of its target NDRG13 at S336 sustains mitochondrial fission and respiratory sufficiency. Timelapse imaging reveals that wildtype NDRG1, but not phosphorylation-deficient NDRG1S336A mutant, engages with mitochondria to facilitate its scission. Using proteomics, and an siRNA screen, we show that mTORC2-phosphorylated NDRG1 cooperates with the small GTPase Cdc424 and Cdc42-specific effectors and regulators to orchestrate fission. Accordingly, RictorKO, NDRG1S336A mutants, and Cdc42-deficient cells each display mitochondrial phenotypes reminiscent of fission failure. During nutrient surplus, mTOR complexes perform anabolic functions5; however, paradoxical reactivation of mTORC2 during fasting plays an unexpected role in driving mitochondrial fission and respiration.

cell biology↗

bioRxiv2022

An oblique plane microscope for mesoscopic imaging of freely moving organisms with cellular resolution

Several important questions in biology require non-invasive and three-dimensional imaging techniques with appropriate spatiotemporal resolution that permit live organisms to move in an unconstrained fashion over an extended field-of-view. While selective-plane illumination microscopy (SPIM) has emerged as a powerful method to observe live biological specimens at high spatio-temporal resolution, typical implementations often necessitate constraining sample mounting or lack the required volumetric speed. Here, we report on an open-top, dual-objective oblique plane microscope (OPM) capable of observing millimeter sized, freely moving animals at cellular resolution. We demonstrate the capabilities of our mesoscopic OPM (MesOPM) by imaging the behavioural dynamics of the sea anemone Nematostella vectensis over 1.56 x 1.56 x 0.25 mm at 1.5 x 2.8 x 5.3{micro}m resolution and 0.5Hz volume rate.

bioengineering↗

bioRxiv2022

Optimal transport analysis of single-cell transcriptomics directs hypotheses prioritization and validation

The explosive growth of regulatory hypotheses from single-cell datasets demands accurate prioritization of hypotheses for in vivo validation. However, current computational methods emphasize overall accuracy in regulatory network reconstruction rather than prioritizing a limited set of causal transcription factors (TFs) that can be feasibly tested. We developed Haystack, a hybrid computational-biological algorithm that combines active learning and the concept of optimal transport theory to nominate and validate high-confidence causal hypotheses. Our novel approach efficiently identifies and prioritizes transient but causally-active TFs in cell lineages. We applied Haystack to single-cell observations, guiding efficient and cost-effective in vivo validations that reveal causal mechanisms of cell differentiation in Drosophila gut and blood lineages. Notably, all the TFs shortlisted for the final, imaging-based assays were validated as drivers of differentiation. Haystacks hypothesis-prioritization approach will be crucial for validating concrete discoveries from the increasingly vast collection of low-confidence hypotheses from single-cell transcriptomics.

bioinformatics↗

bioRxiv2022

Supervised machine learning with feature selection for prioritization of targets related to time-based cellular dysfunction in aging

BackgroundGlobal life expectancy has been increasing without a corresponding increase in health span and with greater risk for aging-associated diseases such as Alzheimers disease (AD). An urgent need to delay the onset of aging-associated diseases has arisen and a dramatic increase in the number of potential molecular targets has led to the challenge of prioritizing targets to promote successful aging. Here, we developed a pipeline to prioritize aging-related genes which integrates the plethora of publicly available genomic, transcriptomic, proteomic and morphological data of C. elegans by applying a supervised machine learning approach. Additionally, a unique biological post-processing analysis of the computational output was performed to better reveal the prioritized genes function within the context of pathways and processes involved in aging across the lifespan of C. elegans. ResultsFour known aging-related genes -- daf-2, involved in insulin signaling; let-363 and rsks-1, involved in mTOR signaling; age-1, involved in PI3 kinase signaling -- were present in the top 10% of 4380 ranked genes related to different markers of cellular dysfunction, validating the computational output. Further, our ranked output showed that 91% of the top 438 ranked genes consisted of known genes on GenAge, while the remaining genes had thus far not yet been associated with aging-related processes. ConclusionThese ranked genes can be translated to known human orthologs potentially uncovering previously unknown information about the basic aging processes in humans. These genes (and their downstream pathways) could also serve as targets against aging-related diseases, such as AD.

bioinformatics↗

bioRxiv2022

Candidate effector proteins from the maize tar spot pathogen Phyllachora maydis localize to diverse plant cell compartments

Most fungal pathogens secrete effector proteins into host cells to modulate their immune responses, thereby promoting pathogenesis and fungal growth. One such fungal pathogen is the ascomycete Phyllachora maydis, which causes tar spot disease on leaves of maize (Zea mays). Sequencing of the P. maydis genome revealed 462 putatively secreted proteins of which 40 contain expected effector-like sequence characteristics. However, the subcellular compartments targeted by P. maydis effector candidate (PmECs) proteins remain unknown and it will be important to prioritize them for further functional characterization. To test the hypothesis that PmECs target diverse subcellular compartments, cellular locations of super Yellow Fluorescent Protein (sYFP)-tagged P. maydis effector candidate proteins were identified using a Nicotiana benthamiana-based heterologous expression system. Immunoblot analyses showed that most of the PmEC-fluorescent protein fusions accumulated protein in N. benthamiana, indicating the candidate effectors could be expressed in dicot leaf cells. Laser-scanning confocal microscopy of N. benthamiana epidermal cells revealed most of the P. maydis putative effectors localized to the nucleus and cytosol. One candidate effector, PmEC01597, localized to multiple subcellular compartments including the nucleus, nucleolus, and plasma membrane while an additional putative effector, PmEC03792, preferentially labelled both the nucleus and nucleolus. Intriguingly, one candidate effector, PmEC04573, consistently localized to the stroma of chloroplasts as well as stroma-containing tubules (stromules). Collectively, these data suggest effector candidate proteins from P. maydis target diverse cellular organelles and may thus provide valuable insights into their putative functions as well as host processes potentially manipulated by this fungal pathogen.

plant biology↗

bioRxiv2022

Connecting human voice profiling to genomics: A predictive algorithm for linking speech phenotypes to genetic microdeletion syndromes

Changes in vocal acoustic patterns are known to correlate with the occurrence of several diseases and syndromes, many of which do not directly affect the structures or processes that control voice production. In such cases, it is difficult to support the existence of correlated changes in voice. This paper presents a methodology for identifying potential genomic bases for such correlations, by finding links between specific genes involved in the conditions under study, and those involved in voice, speech or language generation. Syndromes associated with chromosomal microdeletions are examined as an illustrative case, with focus on their linkage to the FOXP2 gene which has been strongly implicated in speech and language disorders. A novel path-finding graph algorithm to detect pathway chains that connect the the former to the latter is proposed. Statistical analysis of ensembles of "voice" chains detected by this algorithm indicates that they are predictive of speech phenotypes for the syndromes. Algorithmic findings are validated against clinical findings in the literature pertaining to the actual speech phenotypes that have been found to be associated with these syndromes. This methodology may also potentially be used to predict the existence of voice biomarkers in naive cases where the existence of voice biomarkers has not already been established.

bioinformatics↗