Biology subjects

Baker, D.

Publications and source records attributed to Baker, D..

At least 253 records · Page 14Linked to original sources

bioRxiv2020

Structural and functional evaluation of de novo-designed, two-component nanoparticle carriers for HIV Env trimer immunogens

Two-component, self-assembling nanoparticles represent a versatile platform for multivalent presentation of viral antigens. Nanoparticles of different sizes and geometries can be designed and combined with appropriate antigens to fit the requirements of different immunization strategies. Here, we describe detailed antigenic, structural, and functional characterization of computationally designed tetrahedral, octahedral, and icosahedral nanoparticle immunogens displaying trimeric HIV envelope glycoprotein (Env) ectodomains. Env trimers, based on subtype A (BG505) or consensus group M (ConM) sequences and engineered with SOSIP stabilizing mutations, were fused to the underlying trimeric building block of each nanoparticle. Initial screening yielded one icosahedral and two tetrahedral nanoparticle candidates, capable of presenting twenty or four copies of the Env trimer. A number of analyses, including detailed structural characterization by cryo-EM, demonstrated that the nanoparticle immunogens possessed the intended structural and antigenic properties. Comparing the humoral responses elicited by ConM-SOSIP trimers presented on a two-component tetrahedral nanoparticle to the corresponding soluble protein revealed that multivalent presentation increased the proportion of the overall antibody response directed against autologous neutralizing Ab epitopes present on the ConM-SOSIP trimers. Author SummaryProtein constructs based on soluble ectodomains of HIV glycoprotein (Env) trimers are the basis of many current HIV vaccine platforms. Multivalent antigen display is one strategy applied to improve the immunogenicity of different subunit vaccine candidates. Here, we describe and comprehensively evaluate a library of de novo designed, protein nanoparticles of different geometries for their ability to present trimeric Env antigens. We found three nanoparticle candidates that can stably incorporate model Env trimer on their surface while maintaining its structure and antigenicity. Immunogenicity of the designed nanoparticles is assessed in vitro and in vivo. In addition to introducing a novel set of reagents for multivalent display of Env trimers, this work provides both guiding principles and a detailed experimental roadmap for the generation, characterization, and optimization of Env-presenting, self-assembling nanoparticle immunogens.

immunology↗

bioRxiv2020

Tailored Design of Protein Nanoparticle Scaffolds for Multivalent Presentation of Viral Glycoprotein Antigens

The adaptive immune system is highly sensitive to arrayed antigens, and multivalent display of viral glycoproteins on symmetric scaffolds has been found to substantially increase the elicitation of antigen-specific antibodies. Motivated by the considerable promise of this strategy for next-generation anti-viral vaccines, we set out to design new self-assembling protein nanoparticles with geometries specifically tailored to scaffold ectodomains of different viral glycoproteins. We first designed and characterized homo-trimers from designed repeat proteins with N-terminal helices positioned to match the C termini of several viral glycoprotein trimers. Oligomers found to experimentally adopt the designed configuration were then used to generate nanoparticles with tetrahedral, octahedral, or icosahedral symmetry. Examples of all three target symmetries were experimentally validated by cryo-electron microscopy and several were assessed for their ability to display viral glycoproteins via genetic fusion. Electron microscopy and antibody binding experiments demonstrated that the designed nanoparticles display conformationally intact native-like HIV-1 Env, influenza hemagglutinin, and prefusion RSV F trimers in the predicted geometries. This work demonstrates that novel nanoparticle immunogens can be designed from the bottom up with atomic-level accuracy and provides a general strategy for precisely controlling epitope presentation and accessibility.

synthetic biology↗

bioRxiv2020

Summary-data-based mendelian randomisation reveals druggable targets for multiple sclerosis

BackgroundMultiple Sclerosis (MS) is a complex autoimmune disease caused by a combination of genetic and environmental factors. Translation of Genome-Wide Association Study (GWAS) findings in MS into therapeutics and effective preventive strategies has been limited to date. MethodsWe used Summary Data-Based Mendelian Randomisation (SMR) to synthesise findings from public expression quantitative trait locus (eQTL; eQTLgen and CAGE), methylation quantitative trait locus (mQTL; Lothian Birth Cohort and Brisbane Systems Genetics Study), and MS GWAS datasets (International Multiple Sclerosis Genetics Consortium). By correlating the effects of methylation on MS (M-2-MS), methylation on expression (M-2-E), and expression on MS susceptibility (E-2-MS), we prioritise genetic loci with strong evidence of causally influencing MS susceptibility. We overlay these findings onto a list of druggable genes, i.e. genes which are currently, or could theoretically, be targeted by therapeutic compounds. We use GeNets and STRING to identify protein-protein interactions and druggable pathways enriched in our results. We extend these findings to a model of Epstein-Barr Virus-infected B cells, Lymphoblastoid Cell Lines (LCLs). We conducted a systematic review of prioritised genes using the Open Targets platform to identify completed and planned trials targeted prioritised genes in MS and related disease areas. ResultsExpression of 45 genes in peripheral was strongly associated with MS susceptibility (False discovery rate 0.05). Of these 45 genes, 20 encode a protein which is currently targeted by an existing therapeutic compound. These genes were enriched for Gene Ontology terms pertaining to immune system function and leukocyte signalling. We refined this prioritised gene list by restricting to loci where CpG site methylation was associated with MS susceptibility (M-2-MS), with gene expression (M-2-E), and where expression was associated with MS susceptibility (E-2-MS). This approach yielded a list of 15 prioritised druggable target genes for which there was evidence of a causal pathway linking methylation, expression, and MS. Five of these 15 genes are targeted by existing drugs (CD40, ERBB2, VEGFB, MERTK, and PARP1), and three were replicated in a smaller eQTL dataset (CD40, MERTK, and PARP1). In LCLs, SMR prioritised 7 druggable gene targets, of which only one was priortised by the multi-omic approach in peripheral blood (FCRL3). Systematic review of Open Targets revealed multiple early-phase trials targeting 13/20 prioritised genes in disorders related to MS. ConclusionsWe use public datasets and SMR to identify a list of prioritised druggable genetic targets in Multiple Sclerosis. We hope our findings could be translated into effective repurposing of existing drugs to provide novel therapies for MS and, potentially, provide a platform for developing preventive therapies.

genetics↗

bioRxiv2019

Improved protein structure prediction using predicted inter-residue orientations

The prediction of inter-residue contacts and distances from co-evolutionary data using deep learning has considerably advanced protein structure prediction. Here we build on these advances by developing a deep residual network for predicting inter-residue orientations in addition to distances, and a Rosetta constrained energy minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on CASP13 and CAMEO derived sets, the method outperforms all previously described structure prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo designed proteins, identifying the key fold determining residues and providing an independent quantitative measure of the "ideality" of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.

bioinformatics↗

bioRxiv2019

Antibody Targeting of B7-H4 Enhances the Immune Response in Urothelial Carcinoma

Locally advanced urothelial carcinoma has a poor survival despite a response to immunotherapy in approximately 25% of patients. To develop new therapies targeting other immune checkpoints, we identified increased expression of the T cell inhibitor protein, B7-H4 (VTCN1, B7S1, B7X), during tumor development of murine bladder cancer. Evaluation of B7-H4 in human bladder cancer by single-cell RNA-Seq and immune mass cytometry showed that B7-H4 is expressed by luminal tumors that are not normally responsive to PD-1 inhibitors. Additionally, overexpression B7-H4 was associated with significantly worse patient survival. In support of clinical translation, treatment of human monocyte and T cell co-cultures with a B7-H4 blocking antibody resulted in enhanced IFN-{gamma} secretion by CD4+ and CD8+ T cell. While the study of B7-H4 in mouse cancer models has been difficult using tumor cell lines, our findings show that B7-H4 expression increased at 3 months after exposure to BBN on CD11b+ monocytes/macrophages and delivery of anti-B7-H4 antibody resulted in decreased tumor size and increased CD8 immune cell infiltration with increased CD8+/IFN-{gamma}-producing T cells and a complimentary decrease in tumor infiltrating T regulatory cells (Tregs). Furthermore, treatment with a combination of anti-PD-1 and anti-B7-H4 antibodies resulted in a significant reduction in tumor stage. This data suggests that novel anti-B7-H4 antibodies maybe a viable target for bladder cancers unresponsive to PD-1 checkpoint inhibitors.

cancer biology↗

bioRxiv2019

Sequencing smart: De novo sequencing and assembly approaches for non-model mammals.

BackgroundWhilst much sequencing effort has focused on key mammalian model organisms such as mouse and human, little is known about the correlation between genome sequencing techniques for non-model mammals and genome assembly quality. This is especially relevant to non-model mammals, where the samples to be sequenced are often degraded and low quality. A key aspect when planning a genome project is the choice of sequencing data to generate. This decision is driven by several factors, including the biological questions being asked, the quality of DNA available, and the availability of funds. Cutting-edge sequencing technologies now make it possible to achieve highly contiguous, chromosome-level genome assemblies, but relies on good quality high-molecular-weight DNA. The funds to generate and combining these data are often only available within large consortiums and sequencing initiatives, and are often not affordable for many independent research groups. For many researchers, value-for-money is a key factor when considering the generation of genomic sequencing data. Here we use a range of different genomic technologies generated from a roadkill European Polecat (Mustela putorius) to assess various assembly techniques on this low-quality sample. We evaluated different approaches for de novo assemblies and discuss their value in relation to biological analyses.\n\nResultsGenerally, assemblies containing more data types achieved better scores in our ranking system. However, when accounting for misassemblies, this was not always the case for Bionano and low-coverage 10x Genomics (for scaffolding only). We also find that the extra cost associated with combining multiple data types is not necessarily associated with better genome assemblies.\n\nConclusionsThe high degree of variability between each de novo assembly method (assessed from the seven key metrics) highlights the importance of carefully devising the sequencing strategy to be able to carry out the desired analysis. Adding more data to genome assemblies not always results in better assemblies so it is important to understand the nuances of genomic data integration explained here, in order to obtain cost-effective value-for-money when sequencing genomes.

genomics↗

bioRxiv2019

Efficient RNA-mediated reprogramming of human somatic cells to naive pluripotency facilitated by tankyrase inhibition

In contrast to conventional human pluripotent stem cells (hPSC) that are related to post-implantation embryo stages, naive hPSC exhibit features of pre-implantation epiblast. Naive hPSC are established by resetting conventional hPSC, or are derived from dissociated embryo inner cell masses. Here we investigate conditions for transgene-free reprogramming of human somatic cells to naive pluripotency. We find that tankyrase inhibition promotes RNA-mediated induction of naive pluripotency. We demonstrate application to independent human fibroblast cultures and endothelial progenitor cells. We show that induced naive hPSC can be clonally expanded with a diploid karyotype and undergo somatic lineage differentiation following formative transition. Induced naive hPSC lines exhibit distinctive surface marker, transcriptome, and methylome properties of naive epiblast identity. This system for efficient, facile, and reliable induction of transgene free naive hPSC offers a robust platform, both for delineation of human reprogramming trajectories and for evaluating the attributes of isogenic naive versus conventional hPSC.

developmental biology↗

bioRxiv2019

De novo design of proteins with two isoenergetic but structurally divergent ground states

The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used to de novo design proteins that fold to a single state with a deep free energy minima (Huang et al., 2016), and to reengineer natural proteins to alter their dynamics (Davey et al., 2017) or fold (Alexander et al., 2009), the de novo design of closely related sequences which adopt well-defined, but structurally divergent structures remains an outstanding challenge. Here, we design closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations -- one short ([~]66 [A] height) and the other long ([~]100 [A] height) -- reminiscent of the conformational transition of viral fusion proteins (Ivanovic et al., 2013; Podbilewicz, 2014; Skehel and Wiley, 2000). Crystallographic and NMR spectroscopic characterization show that both the short and long state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large scale conformational switches between structurally divergent forms.

biochemistry↗

bioRxiv2019

Analysis of Genetically Regulated Gene Expression identifies a trauma type specific PTSD gene, SNRNP35

PTSD has significant genetic heritability; however, it is unclear how genetic risk influences tissue-specific gene expression. We used brain and non-brain transcriptomic imputation models to impute genetically regulated gene expression (GReX) in 9,087 PTSD-cases and 23,811 controls and identified thirteen significant GReX-PTSD associations. The results suggest substantial genetic heterogeneity between civilian and military PTSD cohorts. The top study-wide significant PTSD-association was with predicted downregulation of the Small Nuclear Ribonucleoprotein U11/U12 Subunit 35 (SNRNP35) in the BA9 region of the prefrontal cortex (PFC) in military cohorts. In peripheral leukocytes from 175 U.S. Marines, the observed PTSD differential gene expression correlated with the predicted blood GReX differences for these individuals, and deployment stress downregulated SNRNP35 expression, primarily in Marines with post-deployment PTSD. SNRNP35 is a subunit of the minor spliceosome complex and SNRNP35 knockdown in cells validated its functional importance in U12-intron splicing. Finally, mimicking acute activation of the endogenous stress axis in mice downregulated PFC Snrnp35 expression.

genetics↗

bioRxiv2018

Dynamic properties of internal noise probed by modulating binocular rivalry

Neural systems are inherently noisy, and this noise can affect our perception from moment to moment. This is particularly apparent in binocular rivalry, where our perception of competing stimuli shown to the left and right eyes alternates over time in a seemingly random fashion. We investigated internal noise using binocular rivalry by modulating rivalling stimuli using dynamic sequences of external noise of various rates and amplitudes. As well as measuring the effect on dominance durations, we repeated each external noise sequence twice, and assessed the consistency of percepts across repetitions. External noise modulations with standard deviations above 4% contrast increased consistency scores above baseline, and were most effective at 1/8Hz. A computational model of rivalry in which internal noise has a 1/f (pink) temporal amplitude spectrum, and a standard deviation of 16%, provided the best account of our data, and was able to correctly predict perception in additional conditions. Our novel technique provides detailed estimates of the dynamic properties of internal noise during binocular rivalry, and by extension the stochastic processes that drive our perception and other types of spontaneous brain activity.\n\nSignificance statementAlthough our perception of the world appears constant, sensory representations are variable because of the noisy nature of biological neurons. Here we used a binocular rivalry paradigm, in which conflicting images are shown to the two eyes, to probe the properties of this internal variability. Using a novel paradigm in which the contrasts of rivalling stimuli are modulated by two independent external noise streams, we infer the amplitude and character of this internal noise. The temporal amplitude spectrum of the noise has a 1/f spectrum, similar to that of natural visual input, and consistent with the idea that the visual system evolved to match its environment.

neuroscience↗

bioRxiv2018

Noninvasive Vagus Nerve Stimulation Alters Neural Response and Physiological Autonomic Tone to Noxious Thermal Challenge

The mechanisms by which noninvasive vagal nerve stimulation (nVNS) affect central and peripheral neural circuits that subserve pain and autonomic physiology are not clear, and thus remain an area of intense investigation. Effects of nVNS vs sham stimulation on subject responses to five noxious thermal stimuli (applied to left lower extremity), were measured in 30 healthy subjects (n=15 sham and n=15 nVNS), with fMRI and physiological galvanic skin response (GSR). With repeated noxious thermal stimuli a group x time analysis showed a significantly (p < .001) decreased response with nVNS in bilateral primary and secondary somatosensory cortices (SI and SII), left dorsoposterior insular cortex, bilateral paracentral lobule, bilateral medial dorsal thalamus, right anterior cingulate cortex, and right orbitofrontal cortex. A group x time x GSR analysis showed a significantly decreased response in nVNS group (p < .0005) in bilaterally in SI, lower and mid medullary brainstem, and inferior occipital cortex. Finally, nVNS treatment showed decreased activity in pronociceptive brainstem nuclei (e.g. the reticular nucleus and rostral ventromedial medulla) and key autonomic integration nuclei (e.g. the rostroventrolateral medulla, nucleus ambiguous, and dorsal motor nucleus of the vagus nerve). In aggregate, noninvasive vagal nerve stimulation reduced the physiological response to noxious thermal stimuli and impacted neural circuits important for pain processing and autonomic output.

neuroscience↗

bioRxiv2018

Internal noise in contrast discrimination propagates forwards from early visual cortex

Human contrast discrimination performance is limited by transduction nonlinearities and variability of the neural representation (noise). Whereas the nonlinearities have been well-characterised, there is less agreement about the specifics of internal noise. Psychophysical models assume that it impacts late in sensory processing, whereas neuroimaging and intracranial electrophysiology studies suggest that the noise is much earlier. We investigated whether perceptually-relevant internal noise arises in early visual areas or later decision making areas. We recorded EEG and MEG during a two-interval-forced-choice contrast discrimination task and used multivariate pattern analysis to decode target/non-target and selected/non-selected intervals from evoked responses. We found that perceptual decisions could be decoded from both EEG and MEG signals, even when the stimuli in both intervals were physically identical. Above-chance decision classification started <100ms after stimulus onset, suggesting that neural noise affects sensory signals early in the visual pathway. Classification accuracy increased over time, peaking at >500ms. Applying multivariate analysis to separate anatomically-defined brain regions in MEG source space, we found that occipital regions were informative early on but then information spreads forwards across parietal and frontal regions. This is consistent with neural noise affecting sensory processing at multiple stages of perceptual decision making. We suggest how early sensory noise might be resolved with Birdsalls linearisation, in which a dominant noise source obscures subsequent nonlinearities, to allow the visual system to preserve the wide dynamic range of early areas whilst still benefitting from contrast-invariance at later stages. A preprint of this work is available at: http://dx.doi.org/10.1101/364612

neuroscience↗

bioRxiv2018

Antibody responses to the Zika virus polyprotein in pregnant and non-pregnant macaques

The specificity of the antibody response against Zika virus (ZIKV) is not well-characterized. This is due, in part, to the antigenic similarity between ZIKV and closely related dengue virus (DENV) serotypes. Since these and other similar viruses co-circulate, are spread by the same mosquito species, and can cause similar acute clinical syndromes, it is difficult to disentangle ZIKV-specific antibody responses from responses to closely-related arboviruses in humans. Here we use high-density peptide microarrays to profile anti-ZIKV antibody reactivity in pregnant and non-pregnant macaque monkeys with known exposure histories and compare these results to reactivity following DENV infection. We also compare cross-reactive binding of ZIKV-immune sera to the full proteomes of 28 arboviruses. We independently confirm a purported ZIKV-specific IgG antibody response targeting ZIKV nonstructural protein 2B (NS2B) that was recently reported in ZIKV-infected people and we show that antibody reactivity in pregnant animals can be detected as late as 127 days post-infection (dpi). However, we also show that these responses wane over time, sometimes rapidly, and in one case the response was elicited following DENV infection in a previously ZIKV-exposed animal. These results suggest epidemiologic studies assessing seroprevalence of ZIKV immunity using linear epitope-based strategies will remain challenging to interpret due to susceptibility to false positive results. However, the method used here demonstrates the potential for rapid profiling of proteome-wide antibody responses to a myriad of neglected diseases simultaneously and may be especially useful for distinguishing antibody reactivity among closely related pathogens.\n\nAuthor summaryZIKV has emerged as a vector-borne pathogen capable of causing serious illness in infected adults and congenital birth defects. The vulnerability of communities to future ZIKV outbreaks will depend, in part, on the prevalence and longevity of protective immunity, thought to be mediated principally by antibodies. We currently lack diagnostic assays able to differentiate ZIKV-specific antibodies from antibodies produced following infection with closely related DENV, and we do not know how long anti-ZIKV responses are detectable. Here we profile antibodies recognizing linear epitopes throughout the entire ZIKV polyprotein, and we profile cross-reactivity with the proteomes of other co-endemic arboviruses. We show that while ZIKV-specific antibody binding can be detected, these responses are generally weak and ephemeral, and false positives may arise through DENV infection. This may complicate efforts to discern ZIKV infection and to determine ZIKV seroprevalence using linear epitope-based assays. The method used in this study, however, has promise as a tool for profiling antibody responses for a broad array of neglected tropical diseases and other pathogens and in distinguishing serology of closely-related viruses.

microbiology↗

bioRxiv2018

Binaural fusion involves weak interaural suppression

The brain combines sounds from the two ears, but what is the algorithm used to achieve this summation of signals? Here we combine psychophysical amplitude modulation discrimination and steady-state electroencephalography (EEG) data to investigate the architecture of binaural combination for amplitude-modulated tones. Discrimination thresholds followed a dipper shaped function of pedestal modulation depth, and were consistently lower for binaural than monaural presentation of modulated tones. The EEG responses were greater for binaural than monaural presentation of modulated tones, and when a masker was presented to one ear, it produced only weak suppression of the response to a signal presented to the other ear. Both data sets were well-fit by a computational model originally derived for visual signal combination, but with suppression between the two channels (ears) being much weaker than in binocular vision. We suggest that the distinct ecological constraints on vision and hearing can explain this difference, if it is assumed that the brain avoids over-representing sensory signals originating from a single object. These findings position our understanding of binaural summation in a broader context of work on sensory signal combination in the brain, and delineate the similarities and differences between vision and hearing.

neuroscience↗

bioRxiv2017

Community-driven data analysis training for biology

The primary problem with the explosion of biomedical datasets is not the data itself, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web-browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences.

bioinformatics↗

bioRxiv2017

A critical comparison of technologies for a plant genome sequencing project

A high quality genome sequence of your model organism is an essential starting point for many studies. Old clone based methods are slow and expensive, whereas faster, cheaper short read only assemblies can be incomplete and highly fragmented, which minimises their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, human. However, plant genomes can be much more repetitive and larger than human, and plant biology makes obtaining high quality DNA free from contaminants difficult. Reflecting their challenging nature we observe that plant genome assembly statistics are typically poorer than for vertebrates. Here we compare Illumina short read, PacBio long read, 10x Genomics linked reads, Dovetail Hi-C and BioNano Genomics optical maps, singly and combined, in producing high quality long range genome assemblies of the potato species S. verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA, compute requirements and sequencing costs. We expect our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.

genomics↗

bioRxiv2017

Epigenetic resetting of human pluripotency

Much attention has focussed on conversion of human pluripotent stem cells (PSC) to a more naive developmental status. Here we provide a method for resetting via transient histone deacetylase inhibition. The protocol is effective across multiple PSC lines and can proceed without karyotype change. Reset cells can be expanded without feeders with a doubling time of around 24 hours. WNT inhibition stabilises the resetting process. The transcriptome of reset cells diverges markedly from primed PSC and shares features with human inner cell mass (ICM). Reset cells activate expression of primate-specific transposable elements. DNA methylation is globally reduced to the level in the ICM but is non-random, with gain of methylation at specific loci. Methylation imprints are mostly lost, however. Reset cells can be re-primed to undergo tri-lineage differentiation and germline specification. In female reset cells, appearance of bi-allelic X-linked gene transcription indicates re-activation of the silenced X chromosome. On re-conversion to primed status, XIST-induced silencing restores monoallelic gene expression. The facile and robust conversion routine with accompanying data resources will enable widespread utilisation, interrogation, and refinement of candidate naive cells.

developmental biology↗

bioRxiv2017

High-Throughput Characterization of Protein-Protein Interactions by Reprogramming Yeast Mating

High-throughput methods for screening protein-protein interactions (PPIs) enable the rapid characterization of engineered binding proteins and interaction networks. While existing methods are powerful, none allow quantitative library-on-library characterization of PPIs in a modifiable extracellular environment. Here, we show that sexual agglutination of S. cerevisiae can be reprogrammed to link PPI strength with mating efficiency using yeast synthetic agglutination (YSA). Validation of YSA with 96 previously characterized interactions shows a strong log-linear relationship between mating efficiency and PPI strength for interactions with KDs ranging from 500 pM to 25 M. Using induced chromosomal translocation to pair barcodes representing interacting proteins, thousands of distinct interactions can be screened in a single pot. YSA binding interactions occur in a controllable extracellular environment, and thus studying the effects of environmental factors on PPI networks is possible. YSA enables the high-throughput, quantitative characterization of PPI networks in a fully defined extracellular environment at a library-on-library scale.

synthetic biology↗