Biology subjects

Goldstein, R. A.

Publications and source records attributed to Goldstein, R. A..

9 recordsLinked to original sources

bioRxiv2026

How are evolutionarily young and old proteins distributed in sequence space?

Protein sequence space is vast due to the combinatorial diversity of 20 amino acids. However, evolution has generated a limited set of "old" canonical protein families sharing evolutionary ancestry, structures and functions. It remains unclear how canonical sequences are placed in sequence space, how recently evolved "young" proteins compare to them, and whether random, young, and canonical sequences can interconvert along evolutionarily plausible paths, and which biophysical properties distinguish or link these sequences. Here, we analyse naturally occurring de novo proteins from yeast and flies, which originate from non-coding DNA and thus have experienced limited evolutionary selection. They serve as a model for examining the relationships between young de novo and intergenic proteins, older canonical proteins, and their randomized counterparts. Because de novo and randomized sequences lack detectable homology, we use an alignment-free k-mer-based distance approach. Randomization shifts distance distributions toward expected random behaviour in all classes, but natural, non-randomized sequence classes remain distinct, indicating non-random residue organization. Each class exhibits characteristic k-mer patterns, with de novo proteins clearly separated from both canonical and all randomized sequences. Sequences bridging these classes are frequently predicted to contain transmembrane helices. De novo proteins are thus not random samples of sequence space. Instead, they occupy constrained yet evolutionarily accessible regions defined by residue order and biophysical constraints, suggesting a plausible pathway for the emergence and diversification of new proteins. Significance StatementDespite the vast combinatorial potential of amino acids, evolution has produced only a limited repertoire of canonical proteins with conserved structure and function. How evolutionarily young proteins relate to older canonical proteins, and whether the sequence space between them is traversable, remain unclear. Here, we decompose canonical proteins, intergenic sequences, and recently emerged yeast and fly de novo proteins, together with randomized controls, into short, interpretable fragments (k-mers) and compare them using alignment-free distances. De novo proteins are markedly distinct from both randomized and canonical sequences. Notwithstanding their evolutionary distance, sequences are connected by stepwise paths comprising bridge sequences, often enriched for low-complexity motifs and transmembrane helices, connecting disordered and structured regions of sequence space.

evolutionary biology↗

bioRxiv2022

AYUKA: A toolkit for fast viral genotyping using whole genome sequencing.

Technological advances enabled the frequent use of whole genome sequencing in the clinical microbiology laboratory. While generating data is now easier than ever, the computational resources and expertise required for analysis are still a challenge for clinical applications. Since it is not always possible to collect clinical specimens at the peak viral load, sequencing results are also not always amenable for analysis with bioinformatics pipelines that always require high quality data. Here we present a fast and reliable method, we named AYUKA, for analysis of viral sequencing data that does not require data pre-processing and provides quality control metrics including estimates for sequencing depth and genome coverage, as well as identifying the viral genotypes in a sample and distinguishing mixed infection from recombinants. This method can be applied to any virus where a classification by genotype is employed and determining it is relevant. We generated a validation dataset composed of cultured and sequenced reference adenoviruses from distinct species, that we compared with the gold standard clinical processing pipeline currently implemented to demonstrate reliability. The validation shows better sensitivity than mapping and perfect specificity in detecting the correct genotypes and in a wide range of adenovirus species. Run time was consistently under one minute per sample on a standard laptop, allowing the analysis of more than 100 samples per hour. This open-source method is available at https://github.com/afonsoguerra/AYUKA and precomputed databases are available at https://zenodo.org/record/6521576 allowing analysis of raw data straight from the sequencer within minutes on a standard computer, with minimum setup or expertise required to perform the analysis. The information contained within the AYUKA report can be of use for both the clinical team that collected the sample, but also for guiding the bioinformatics analysis team in the in-depth downstream analyses and genetic epidemiology investigations.

bioinformatics↗

bioRxiv2022

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches to reconstruct outbreaks exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is stable among repeated serial samples from the same host, is transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

evolutionary biology↗

bioRxiv2021

WeightedLD: The Application of Sequence Weights to Linkage Disequilibrium

Sequence-weighting methods are commonly employed to account for biases in sequence datasets. We use a weighting scheme which considers the observed distinctiveness of sequences and apply it to calculations of linkage disequilibrium. Each sequence now contributes a weighted score to linkage disequilibrium measurements of pairwise loci. We demonstrate that this reduces the effect of uneven sampling, as underrepresented groups of sequences will each contribute more individually than redundant, similar sequences. AvailabilitySource code for a python and rust implementation are freely available at under an MIT license at github.com/ojcharles/WeightedLD. Contactr.goldstein@ucl.ac.uk or oscar.charles.18@ucl.ac.uk

genetics↗

bioRxiv2021

SARS-CoV-2 convergent evolution cannot be reliably inferred from phylogenetic analyses

A homoplasy is a trait shared between individuals that did not arise in a common ancestor, but rather is the result of convergent evolution. SARS-CoV-2 homoplasic mutations are important to characterise, because the evidence for a mutation conferring a fitness advantage is strengthened if this mutation has evolved independently and repeatedly in separate viral lineages. Yet detecting homoplasy is difficult due to insufficient variation between sequences to construct reliable phylogenetic trees. Here, we develop a method to more robustly identify confident homoplasies. We derive a maximum likelihood (ML) tree, with taxa bearing seemingly recurrent mutations dispersed across the tree, and then, for each potentially homoplasic mutation, we derive an alternative tree where the same taxa are constrained to one clade such that the mutation is no longer homoplasic. We then compare how well the two trees fit the sequence data. Applying this method to SARS-CoV-2 yields only a few instances where the constrained trees have significantly less statistical support than unconstrained tree, suggesting phylogenetics can provide limited support for homoplasy in SARS-CoV-2 and that caution is needed when inferring evidence of convergent evolution from phylogenetic methods in the absence of evidence from other sources.

evolutionary biology↗

bioRxiv2019

Whole genome sequencing of Herpes Simplex Virus 1 directly from human cerebrospinal fluid reveals selective constraints in neurotropic viruses.

Herpes Simplex Virus type 1 (HSV-1) chronically infects over 70% of the global population. Clinical manifestations are largely restricted to recurrent epidermal vesicles. However, HSV-1 also leads to encephalitis, the infection of the brain parenchyma, with high associated rates of mortality and morbidity. In this study, we performed target enrichment followed by direct sequencing of HSV-1 genomes, using target enrichment methods on the cerebrospinal fluid (CSF) of clinical encephalitis patients and from skin swabs of epidermal vesicles on non-encephalopathic patients. Phylogenetic analysis revealed high inter-host diversity and little population structure. By contrast, samples from different lesions in the same patient clustered with similar patterns of allelic variants. Comparison of consensus genome sequences shows HSV-1 has been freely recombining, except for distinct islands of linkage disequilibrium (LD). This suggests functional constraints prevent recombination between certain genes, notably those encoding pairs of interacting proteins. Distinct LD patterns characterised subsets of viruses recovered from CSF and skin lesions, which may reflect different evolutionary constraints in different body compartments. Functions of genes under differential constraint related to immunity or tropism and provide new hypotheses on tissue-specific mechanisms of viral infection and latency.

evolutionary biology↗

bioRxiv2019

In Vivo Emergence of a Novel Protease Inhibitor Resistance Signature in HIV-1 Matrix

BackgroundProtease Inhibitors (PIs) are the second- and last-line therapy for the majority of HIV-infected patients worldwide. Only around 20% of individuals who fail PI regimens develop major resistance mutations in protease. We sought to explore the role of mutations in gag-protease genotypic and phenotypic changes within six Nigerian patients who failed PI-based regimens without known drug resistance associated protease mutations in order to identify novel determinants of PI resistance. MethodsTarget enrichment and NGS by Illumina Miseq were followed by haplotype reconstruction. Full length gag-protease regions were amplified from baseline (pre-PI) and virologic failure (VF) samples, sequenced and used to construct gag/protease pseudotyped viruses. Phylogenetic analysis was performed using maximum likelihood methods. Susceptibility to lopinavir (LPV) and darunavir (DRV) were measured using a single-cycle replication assay. Western blotting was used to analyse Gag cleavage. ResultsIn one of six participants (subtype CRF02_AG) we found 4-fold lower LPV susceptibility in viral clones during failure of second line treatment. A combination of four mutations (S126del, H127del, T122A and G123E) in p17 matrix of baseline virus generated a similar 4x decrease in susceptibility to LPV but not darunavir. These four amino acid changes were also able to confer LPV resistance to a subtype B gag-protease backbone. Western blotting did not demonstrate significant Gag cleavage differences between sensitive and resistant isolates. Resistant viruses had around 2-fold lower infectivity compared to sensitive clones in the absence of drug. NGS combined with haplotype reconstruction revealed resistant, less fit clones emerged from a minority population at baseline and thereafter persisted alongside sensitive fitter viruses. ConclusionsWe have used a multi-pronged genotypic and phenotypic approach to document emergence and temporal dynamics of a novel protease inhibitor resistance signature in p17 matrix, revealing the interplay between Gag associated resistance and fitness.

microbiology↗

bioRxiv2019

Preadaptation of pandemic GII.4 noroviruses in hidden virus reservoirs years before emergence

The control of pandemic pathogens depends on early prediction of pandemic variants and, more generally, understanding origins of such variants and factors that drive their global spread. This is especially important for GII.4 norovirus, where vaccines under development offer promise to prevent hundreds of millions of annual gastroenteritis cases. Previous studies have suggested that new GII.4 pandemic viruses evolve from previous pandemic variants through substitutions in the antigenic region of the VP1 protein that enable evasion of host population immunity, leading to global spread. In contrast, we show here that the acquisition of new genetic and antigenic characteristics is not the proximal driver of new pandemics. Instead, pandemic GII.4 viruses circulate undetected for years before causing a new pandemic, during which time they diversify and spread over wide geographical areas. Serological data demonstrate that by 2003, some nine years before it emerged as a new pandemic, the ancestral 2012 pandemic strain had already acquired the antigenic characteristics that allowed it to evade prevailing population immunity against the previous 2009 pandemic variant. These results provide strong evidence that viral genetic changes are necessary but not sufficient for GII.4 pandemic spread. Instead, we suggest that it is changes in host population immunity that enable pandemic spread of an antigenically-preadapted GII.4 variant. These results indicate that predicting future GII.4 pandemic variants will require surveillance of currently unsampled reservoir populations. Furthermore, a broadly acting GII.4 vaccine will be critical to prevent future pandemics.\n\nSignificanceNorovirus pandemics and their associated public health and economic costs could be prevented by effective vaccines. However, vaccine development and distribution will require identification of the sources and drivers of new pandemics. We here use phylogenetics and serological experiments to develop and test a new hypothesis of pandemic norovirus emergence. We find that pandemic noroviruses preadapt, diversify and spread worldwide years prior to emergence, strongly indicating that genetic changes are necessary but not sufficient to drive a new pandemic. We instead suggest that changes in population immunity enable pandemic emergence of a pre-adapted low-level variant. These findings indicate that prediction of new pandemics will require surveillance of under-sampled virus reservoirs and that norovirus vaccines will need to elicit broad immunity.

evolutionary biology↗

bioRxiv2018

Haplotype assignment of virus NGS data using co-variation of variant frequencies

Longitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We test this method with synthetic data sets of mixed cytomegalovirus and norovirus genomes, demonstrating high accuracy when longitudinal samples are available.

genomics↗