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Rand, K. D.

Publications and source records attributed to Rand, K. D..

13 recordsLinked to original sources
bioRxiv2024

StarSignDNA: Signature tracing for accurate representation of mutational processes

All cell lineages accumulate mutations over time, increasing the probability that some lineages eventually become malignant. Many of the processes responsible for generating mutations are leaving a characteristic footprint in the genome that allows their presence to be detected. However, the mutational pattern in a tumour is usually the combined result of multiple mutational processes being at work simultaneously, and the problem of disentangling the different footprints and their relative impact then becomes a deconvolution problem. Several algorithms have been developed for this purpose, most of them involving a factorization of the mutation count matrix into two non-negative matrices, representing respectively the underlying mutational signatures and the relative weighting of (or exposure to) these signatures. Here, we introduce the StarSignDNA algorithm for mutational signature analysis, which offers efficient re-fitting and de novo mutational signature extraction. StarSignDNA is capable of deciphering well-differentiated signatures linked to known mutagenic mechanisms and suggesting clinically relevant predictions for a single patient. The package offers a command line-based interface and data visualization routines. Author summaryStarSignDNA is a novel algorithm for identifying mutational signatures from cancer sequencing data. It excels in low mutation count scenarios, balancing signature detection and true signature discovery. StarSignDNA improves prediction accuracy and biological validity by addressing challenges such as overfitting and underfitting, achieving optimal variable selection and shrinkage, and ensuring interpretability. In re-fitting, it reduces prediction variance and handles sparsity, resulting in more precise predictions. In de novo extraction, it improves the detection of challenging signatures and achieves better alignment between detected and known signatures through unsupervised cross-validation. Its unique features, including prediction confidence and customizable reference signatures, offer valuable insights for clinical single-sample analysis.

bioinformatics↗
bioRxiv2024

Structure and dynamics of the autoantigen GAD65 in complex with the human autoimmune polyendocrine syndrome type 2-associated autoantibody b96.11

The enzyme glutamate decarboxylase (GAD) produces the neurotransmitter GABA, using pyridoxal-5-phosphate. GAD exists as two isoforms, GAD65 and GAD67. Only GAD65 acts as a major autoantigen, with its autoantibodies frequently found in type 1 diabetes and other autoimmune diseases. Here we characterize the structure and dynamics of GAD65 and its interaction with the autoimmune polyendocrine syndrome type 2-associated autoantibody b96.11. Combining hydrogen-deuterium exchange mass spectrometry (HDX), X-ray crystallography, cryo-electron microscopy and computational approaches, we dissect the conformational dynamics of the inactive apo- and the active holo-forms of GAD65, as well as the structure of the GAD65-autoantibody complex. HDX reveals the time-resolved, local dynamics that accompany autoinactivation, with the catalytic loop playing a key role in promoting collective dynamics at the interface between CTD and PLP domains. In the GAD65-b96.11 complex, heavy chain CDRs dominate the interaction, with the relatively long CDRH3 at the interface centre and uniquely bridging the GAD65 dimer via extensive electrostatic interactions with the 260PEVKEK265 motif. The autoantibody bridges structural elements on GAD65 that contribute to conformational change in GAD65, thus connecting the unique and intrinsic conformational flexibility that governs the autoinactivation mechanism of the enzyme to its autoantigenicity. The intrinsic dynamics, rather than sequence differences within epitopes, appear to be responsible for the contrasting autoantigenicities of GAD65 and GAD67. Our data thus reveal insights into the structural and dynamic differences between GAD65 and GAD67 that dictate their contrasting autoantibody reactivities, provide a new structural rationalisation for the nature of the autoimmune response to GAD65, and may have broader implications for antigenicity in general.

biochemistry↗
bioRxiv2024

Structural dynamics and immunogenicity of the recombinant and outer membrane vesicle-embedded Meningococcal antigen NadA

The structure and conformation adopted by protein vaccine antigens significantly influence the exposure of their antigenic determinants. Structural knowledge of antigens in native state could drive the design of recombinant vaccines that resemble their cognate native forms, although such information is often difficult to obtain, particularly for membrane proteins. Here, we assessed the structural and functional features of the native Neisseria Adhesin A (NadA), a meningococcal trimeric outer membrane protein included as soluble recombinant antigen in the 4CMenB vaccine. We used hydrogen-deuterium exchange mass spectrometry (HDX-MS) to generate a structural model of NadA and to compare the fold and structural dynamics of the recombinant NadA as soluble vaccine form, and the native NadA in situ, as embedded in meningococcal outer membrane vesicles (OMVs), complementing the HDX data with electron microscopy imaging. While their overall structures are similar, conformational differences between the two forms were observed. Especially, OMV- embedded NadA appears more susceptible to trimer opening than its cognate soluble antigen, suggesting that NadA in its native membrane could display a larger antigenic surface. Accordingly, we show that mice immunized with OMV-embedded NadA elicited antibodies with superior bactericidal activity and capable of better preventing bacterial adhesion compared to the soluble antigen. Collectively, these data support the hypothesis that protein vaccine antigens presented in native-like environments can elicit a more potent immune response than recombinant forms.

biophysics↗
bioRxiv2023

KAGE 2: Fast and accurate genotyping of structural variation using pangenomes

Structural variation is known to play an important and often overlooked role in regulating disease and traits, but accurately detecting structural variants from sequencing data has traditionally been difficult. However, recent improvements in high-quality genome assembly along with methodological advancements in pangenome creation have opened up the landscape for methods that use such pangenomes for structural variant calling and genotyping. We here present KAGE2, which accurately and efficiently genotypes structural variation by exploiting the availability of pangenomes that represent known variation in a population. Through comprehensive benchmarking, we highlight limitations of existing methodology and show that KAGE2 is more accurate and considerably faster than existing methods.

bioinformatics↗
bioRxiv2023

Development of a PNGase Rc column for online deglycosylation of complex glycoproteins during HDX-MS

Protein glycosylation is one of the most common PTMs and many cell surface receptors, extracellular proteins and biopharmaceuticals are glycosylated. However, HDX-MS analysis of such important glycoproteins has so far been limited by difficulties in determining the HDX of the protein segments that contain glycans. We have developed a column containing immobilized PNGase Rc (from Rudaea cellulosilytica) that can readily be implemented into a conventional HDX-MS setup to allow improved analysis of glycoproteins. We show that HDX-MS with the PNGase Rc column enables efficient online removal of N-linked glycans and the determination of the HDX of glycosylated regions in several complex glycoproteins. Additionally, we use the PNGase Rc column to perform a comprehensive HDX-MS mapping of the binding epitope of a mAb to c-Met, a complex glycoprotein drug target. Importantly, the column retains high activity in the presence of common quench-buffer additives like TCEP and urea and performed consistent across 114 days of extensive use. Overall, our work shows that HDX-MS with the integrated PNGase Rc column can enable fast and efficient online deglycosylation at harsh quench conditions to provide comprehensive analysis of complex glycoproteins.

biochemistry↗
bioRxiv2023

Ultra-fast genotyping of SNPs and short indels using GPU acceleration

As decreasing DNA sequencing costs leads to a steadily increasing rate of generated data, the development of efficient algorithms for processing of the sequence data is increasingly important to reduce costs and energy consumption. Recent work have shown that genotyping can be done efficiently and accurately using alignment-free methods that are based on analyzing kmers from sequenced reads. In particular, we have recently presented the KAGE genotyper, which uses an efficient pangenome representation of known individuals in a population to further increase accuracy and efficiency. While existing genotypers like KAGE use the Central Processing Unit (CPU) to count and analyze kmers, the Graphical Processing Unit (GPU) has shown promising for reducing runtime for similar problems. We here present GKAGE, a new and improved version of KAGE that utilizes the GPU to further increase the computational efficiency. This is done by counting and analyzing large amounts of kmers in the many parallel cores of a GPU. We show that GKAGE is, on hardware of comparable cost, able to genotype an individual up to an order of magnitude faster than KAGE while producing the same output, which makes it by far the fastest genotyper available today. GKAGE can run on consumer-grade GPUs, and enables genotyping of a human sample in only a matter of minutes without the need for expensive high-performance computers. GKAGE is open source and available at https://github.com/kage-genotyper/kage.

bioinformatics↗
bioRxiv2022

BioNumPy: Fast and easy analysis of biological data with Python

Python is a popular and widespread programming language for scientific computing, in large part due to the powerful array programming library NumPy, which makes it easy to write clean, vectorized and efficient code for handling large datasets. A challenge with using array programming for biological data is that the data is often non-numeric and variable-length (such as DNA sequences), inhibiting out-of-the-box use of standard array programming techniques. Thus, a tradition in bioinformatics has been to use low-level languages like C and C++ to write efficient code. This makes the tools less transparent to the average computational biologist - making them harder to understand, modify and contribute to. We here present a new Python package BioNumPy, which adds a layer on top of NumPy in order to enable intuitive array programming on biological datasets. BioNumPy is able to efficiently load biological datasets (e.g. FASTQ-files, BED-files and BAM-files) into NumPy-like data structures, so that NumPy operations like indexing, vectorized functions and reductions can be applied to the data. We show that BioNumPy is considerably faster than vanilla Python and other Python packages for common bioinformatics tasks, and in many cases as fast as tools written in C/C++. BioNumPy thus bridges a long-lasting gap in bioinformatics, allowing the same programming language (Python) to be used across the full spectrum from quick and simple scripts to computationally efficient processing of large-scale data.

bioinformatics↗
bioRxiv2021

KAGE: Fast alignment-free graph-based genotyping of SNPs and short indels

Genotyping is a core application of high-throughput sequencing. We present KAGE, a genotyper for SNPs and short indels that is inspired by recent developments within graph-based genome representations and alignment-free methods. KAGE uses a pan-genome representation of the population to efficiently and accurately predict genotypes. Two novel ideas improve both the speed and accuracy: a Bayesian model incorporates genotypes from thousands of individuals to improve prediction accuracy, and a computationally efficient method leverages correlation between variants. We show that the accuracy of KAGE is at par with the best existing alignment-free genotypers, while being an order of magnitude faster.

bioinformatics↗
bioRxiv2019

Assessing graph-based read mappers against a novel baseline approach highlights strengths and weaknesses of the current generation of methods

Graph-based reference genomes have become popular as they allow read mapping and follow-up analyses in settings where the exact haplotypes underlying a high-throughput sequencing experiment are not precisely known. Two recent papers show that mapping to graph-based reference genomes can improve accuracy as compared to methods using linear references. Both of these methods index the sequences for most paths up to a certain length in the graph in order to enable direct mapping of reads containing common variants. However, the combinatorial explosion of possible paths through nearby variants also leads to a huge search space and an increased chance of false positive alignments to highly variable regions. We here assess two prominent graph-based read mappers against a novel hybrid baseline approach that combines an initial path determination with a tuned linear read mapping method. We show, using a previously proposed benchmark, that this simple approach is able to improve accuracy of read-mapping to graph-based reference genomes. Our method is implemented in a tool, Two-step Graph Mapper, which is available at https://github.com/uio-bmi/two_step_graph_mapper along with data and scripts for reproducing the experiments.

bioinformatics↗
bioRxiv2018

Beware the Jaccard: the choice of metric is important and non-trivial in genomic colocalisation analysis.

BackgroundThe generation and systematic collection of genome-wide data is ever-increasing. This vast amount of data has enabled researchers to study relations between a variety of genomic and epigenomic features, including genetic variation, gene regulation, and phenotypic traits. Such relations are typically investigated by comparatively assessing genomic co-occurrence. Technically, this corresponds to assessing the similarity of pairs of genome-wide binary vectors. A variety of metrics have been proposed for this problem in other fields like ecology. However, while several of these metrics have been employed for assessing genomic co-occurrence, their appropriateness for the genomic setting has never been investigated.\n\nResultsWe show that the choice of metric may strongly influence results and propose two alternative modelling assumptions that can be used to guide this choice. On both simulated and real genomic data, the Jaccard index is strongly affected by dataset size and should be used with caution. The Forbes coefficient (fold change) and tetrachoric correlation are less affected by dataset size, but one should be aware of increased variance for small datasets.\n\nAvailabilityAll results on simulated and real data can be inspected and reproduced at: https://hyperbrowser.uio.no/sim-measure

bioinformatics↗
bioRxiv2018

Investigating the conformational response of the Sortilin receptor upon binding endogenous peptide- and protein ligands by HDX-MS

Sortilin is a multifunctional transmembrane neuronal receptor involved in sorting of neurotrophic factors and apoptosis signalling. So far, structural characterization of Sortilin and its endogenous ligands has been limited to crystallographic studies of Sortilin in complex with the neuropeptide Neurotensin. Here, we use hydrogen/deuterium exchange mass spectrometry to investigate the conformational response of Sortilin to binding biological ligands including the peptides Neurotensin and the Sortilin propeptide and the proteins Progranulin and pro-Nerve growth factor-{beta}. The results show that the ligands employ two binding sites inside the cavity of the {beta}-propeller of Sortilin. However, ligands have distinct differences in their conformational impact on the receptor. Interestingly, the protein ligands induce conformational stabilization in a remote membrane-proximal domain, hinting at an unknown conformational link between the ligand binding region and this membrane-proximal region of Sortilin. Our findings improves our molecular understanding of Sortilin and how it mediates diverse ligand-dependent functions important in neurobiology.

biophysics↗
bioRxiv2018

Graph Peak Caller: calling ChIP-Seq Peaks on Graph-based Reference Genomes

Graph-based representations are considered to be the future for reference genomes, as they allow integrated representation of the steadily increasing data on individual variation. Currently available tools allow de novo assembly of graph-based reference genomes, alignment of new read sets to the graph representation as well as certain analyses like variant calling and haplotyping. We here present a first method for calling ChIP-Seq peaks on read data aligned to a graph-based reference genome. The method is a graph generalization of the peak caller MACS2, and is implemented in an open source tool, Graph Peak Caller. By using the existing tool vg to build a pan-genome of Arabidopsis thaliana, we validate our approach by showing that Graph Peak Caller with a pan-genome reference graph can trace variants within peaks that are not part of the linear reference genome, and find peaks that in general are more motif-enriched than those found by MACS2.

bioinformatics↗
bioRxiv2017

Partial Unwinding of Transmembrane Helices Facilitates Alternating Access in the Neurotransmitter:Sodium Symporter LeuT

The prokaryotic neurotransmitter:sodium symporter (NSS) LeuT from Aquifex aeolicus is an established structural model for mammalian NSS counterparts. Here, we investigate the substrate translocation mechanism of LeuT by measuring the solution-phase structural dynamics of the transporter in distinct functional states by hydrogen/deuterium exchange mass spectrometry (HDX-MS). Our HDX-MS data pinpoint LeuT segments involved in substrate transport and reveal for the first time a comprehensive and detailed view of the solution-phase dynamics associated with transition of the transporter between outward- and inwardfacing configurations in a Na+- as well as K+-dependent manner. The results suggest that partial unwinding of transmembrane helices 1/5/6/7 drive LeuT from a substrate-bound, outward-facing occluded conformation towards an inward-facing open state. We thereby envisage that substrate release is facilitated by formation of two distinct solvent pathways, which mediate access to the Na+ and substrate binding sites.\n\nThe neurotransmitter:sodium symporter (NSS) family includes prokaryotic and eukaryotic integral membrane proteins that harness the energy stored in the Na+ concentration gradient to transport solutes across the cell membrane (1, 2). Mammalian NSS proteins play an important role in terminating the neurotransmission in the central nervous system by rapid uptake of neurotransmitters against their concentration gradient into the presynaptic neuron or neighboring glial cells (3-5). Numerous neuropsychiatric conditions are associated with altered function of NSS transporters or low neurotransmitter concentrations in the synaptic cleft (2). Many NSS proteins therefore represent favorable targets for therapeutic drugs that act as potent transport inhibitors to increase neurotransmitter levels at the synaptic junction (2, 6). Despite the importance of mammalian NSS proteins in neurobiology and pharmacology, the molecular mechanisms underlying the transport function of mammalian NSS family members have proven difficult to elucidate by traditional methods as the target proteins are unstable in detergent-solubilized form (7) and difficult to purify in required quantity and purity.\n\nThe prokaryotic NSS protein LeuT from Aquifex aeolicus has emerged as an important structural model to investigate the structure-function relationship of mammalian NSS counterparts (7-9). High-resolution crystal structures of LeuT in distinct functional states (10-13) have established a structural framework and given rise to mechanistic models depicting the substrate transport mechanism (14, 15). LeuT comprises 12 transmembrane segments (TMs) that are interconnected by relatively short extracellular (EL) and intracellular (IL) loops. The first TMs 1-5 share a similar structural repeat with the following TMs 6-10 but are inverted in the membrane plane (10). The specific arrangement of TM domains, also referred to as the 5+5 or LeuT fold (10), has been observed in other NSS proteins (16-18), but also in transporters without sequence homology to LeuT (19, 20), suggesting the possibility of a conserved structural scaffold for many secondary active transporters (8). The primary binding site for the substrate (S1) and residues involved in coordination of two sodium ions (Na1 and Na2) are located approximately halfway across the membrane bilayer in the core of the transporter (10). The characteristic unwound regions of TMs 1 and 6 (providing both TMs with an a- and a b-section) fulfill a dual role in coordinating the sodium ions and forming interactions with the substrate molecule. Individual amino acid residues of TMs 3 and 8 as well as the sodium occupancy in the Na1 site complete the S1 binding pocket.\n\nAccording to the widely embraced alternating access model (21, 22), secondary active transporters isomerize between distinct functional states in a substrate-dependent manner. That is, the substrate binding site is alternatively exposed to either the intracellular or extracellular aqueous environment. X-ray crystallography provided structures of LeuT in outward-facing open (11, 12), outward-facing occluded (10), and inwardfacing open (11) conformations and led to the identification of external and internal gating residues in LeuT and related transporters (23-26). Based on these structural snapshots, it has been hypothesized that local and large-scale structural rearrangements are required to regulate the molecular gates and the outward-to-inward transition of the transporter, respectively (11). Combined evidence from crystallographic, functional, and simulation studies suggest that the underlying allosteric couplings are essential for LeuT to function as a symporter (27). Several key aspects of the transport cycle, in particular the molecular mechanism related to the transition of LeuT to the inward-facing open state, have remained controversial and are the subject of extensive debate (8, 28-30).\n\nHere, we have studied the substrate translocation mechanism of LeuT by measuring the structural dynamics of the protein in solution as a function of time and substrate/ion composition (e.g. leucine, Na+, K+, and Cs+) by local hydrogen/deuterium exchange mass spectrometry (HDX-MS). The exchange of hydrogen to deuterium (HDX) of backbone amides in a protein is dependent on the presence and stability of hydrogen bonds and thus provides a sensitive probe for higher-order structure and dynamics of the target protein in solution (31, 32). HDX-MS is a non-perturbing technique that allows the collection of structural dynamics data along the entire protein backbone in a coherent manner without the need for sequence alterations or changes to the covalent structure of the protein for labeling (33). Briefly, the target protein is diluted into deuterated buffer and labeled for various time intervals. The isotopic exchange reaction is quenched by lowering pH and temperature to approximately 2.5 and 0 {degrees}C, respectively, and the protein subsequently digested using an acid-stable protease (e.g. pepsin). Chromatographic separation and mass analysis of these peptides, in turn, reveal the shift in mass over time (i.e., deuterium uptake) of individual regions of the target protein, which is commonly referred to as local HDX analysis. A more detailed background on the HDX-MS technique and its applications in protein science can be found in several reviews (34-37).\n\nOur HDX-MS measurements provide a detailed map of LeuT regions involved in conformational changes during substrate transport (TMs 1a/1b/2/5/6a/6b/7 and interconnecting loops IL1/EL2/EL3/EL4b) and allow for the first time an unperturbed global view on the structural dynamics associated with the outward-to-inward transition of the wild-type transporter in solution. Of special interest, our acquired HDX data suggest that several helices (TMs 1a/5/6/7 and EL4b) are partially unwound in the course of substrate transport and that these unfolding events are dynamically coupled between individual helices that form the substrate binding site and the cytoplasmic gate. Addition of Na+ or the combination of Na+ and leucine destabilized discrete structural motifs on the extracellular side, stabilized the inner gate of LeuT, and substantially reduced the rate of unfolding in individual TM helices relative to the K+-bound state. We envisage that partial unwinding of TM helices accompanies the outward-to-inward isomerization in LeuT and that the same concept might be relevant to related transporters bearing the LeuT fold, hence extending the general model of NSS transport mechanism. Moreover, we provide additional experimental evidence for a potential role of K+ in the transport cycle as K+ selectively shifted the conformational equilibrium of LeuT in a dose-dependent manner towards an inwardfacing state under physiologically relevant concentrations.

biophysics↗