Biology subjects

Brown, N.

Publications and source records attributed to Brown, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Macrophage-derived developmental endothelial locus 1 (DEL-1) expression promotes an immunoprotective phenotype in experimental visceral leishmaniasis.

The identification of tissue-derived homeostatic molecules regulating immune plasticity is essential for understanding the role of macrophages in immune responses to intra-phagosomal pathogens. Developmental endothelial locus-1 (DEL-1) is a functionally versatile homeostatic factor capable of inhibiting the onset of inflammation and promoting inflammation resolution, but its role in the response to intracellular infections has not been previously addressed. Leishmania, causative agents of the neglected tropical disease leishmaniasis, are intra-phagosomal parasites that establish a replicative niche within macrophages. Here, using a well-established murine model of visceral infection with Leishmania donovani, we establish DEL-1 as a novel regulator of immunity to this infection. Parasite burden was significantly higher in B6.Edil3-/- (Del1-KO) compared to wild type B6 mice, as determined by whole body IVIS imaging, largely as a result of increased liver parasite load. However, lack of DEL-1 enhanced hepatomegaly and enhanced granulomatous inflammation. Conversely, parasite burden and the formation of large granulomas was reduced in mice overexpressing DEL-1 in macrophages but not in endothelial cells. Our findings reveal a hitherto unknown role of DEL-1 in the immune response to L. donovani infection and may represent a novel approach to mitigate immunopathology.

immunology↗

bioRxiv2023

Non-equilibrium distribution of kinesin-streptavidin complexes revealed by Mass Photometry

Kinesin-streptavidin complexes are widely used in microtubule-based active-matter studies. The stoichiometry of the complexes is empirically tuned but experimentally challenging to determine. Here, mass photometry measurements reveal heterogenous distributions of kinesin-streptavidin complexes. Our binding model indicates that heterogeneity arises from both the kinesin-streptavidin mixing ratio and the kinesin-biotinylation efficiency.

biophysics↗

bioRxiv2023

Gut microbiota promotes pain in fibromyalgia

Fibromyalgia is a chronic syndrome characterized by widespread pain in the absence of evident tissue injury or pathology, making it one of the most mysterious chronic pain conditions. Despite affecting 2-4% of the population, primarily women1, the cause and underlying mechanisms of fibromyalgia remain elusive, and effective targeted treatments are currently unavailable. The gut microbiota of women with fibromyalgia differs from healthy controls2,3. However, it is unknown whether changes in gut microbiota have a causal role in mediating pain and other symptoms of fibromyalgia. Here, we show that fecal microbiota transplantation (FMT) from individuals with fibromyalgia, but not from healthy controls, into germ-free mice induces persistent pain hypersensitivity. FMT from fibromyalgia patients led to a reduction in intraepidermal nerve fiber density and alterations in the peripheral immune profile, and induced activation of spinal microglia, which contributed to the development of pain in mice. Notably, the pain hypersensitivity in mice that were administered microbiota from fibromyalgia patients resolved after FMT from healthy controls. Consistent with these findings, an open-label pilot study showed that transplanting microbiota from healthy individuals to humans with fibromyalgia alleviated pain and reduced overall symptom severity. Thus, altered gut microbiota has a causal role in fibromyalgia pain, highlighting it as a promising target for therapeutic interventions.

neuroscience↗

bioRxiv2023

The long and short of it: Benchmarking viromics using Illumina, Nanopore and PacBio sequencing technologies

Viral metagenomics has fuelled a rapid change in our understanding of global viral diversity and ecology. Long-read sequencing and hybrid approaches that combine long and short read technologies are now being widely implemented in bacterial genomics and metagenomics. However, the use of long-read sequencing to investigate viral communities is still in its infancy. While Nanopore and PacBio technologies have been applied to viral metagenomics, it is not known to what extent different technologies will impact the reconstruction of the viral community. Thus, we constructed a mock phage community of previously sequenced phage genomes and sequenced using Illumina, Nanopore, and PacBio sequencing technologies and tested a number of different assembly approaches. When using a single sequencing technology, Illumina assemblies were the best at recovering phage genomes. Nanopore- and PacBio-only assemblies performed poorly in comparison to Illumina in both genome recovery and error rates, which both varied with the assembler used. The best Nanopore assembly had errors that manifested as SNPs and INDELs at frequencies ~4x and 120x higher than found in Illumina only assemblies respectively. While the best PacBio assemblies had SNPs at frequencies ~3.5 x and 12x higher than found in Illumina only assemblies respectively. Despite high read coverage, long-read only assemblies failed to recover a complete genome for any of the 15 phage, down sampling of reads did increase the proportion of a genome that could be assembled into a single contig. Overall the best approach was assembly by a combination of Illumina and Nanopore reads, which reduced error rates to levels comparable with short read only assemblies. When using a single technology, Illumina only was the best approach. The differences in genome recovery and error rates between technology and assembler had downstream impacts on gene prediction, viral prediction, and subsequent estimates of diversity within a sample. These findings will provide a starting point for others in the choice of reads and assembly algorithms for the analysis of viromes. Data SummaryAll reads from virome sequencing were submitted to the ENA under study PRJEB56639. The assemblies are provided via FigShare (https://figshare.com/s/2d9b5121eb421d370455). Author NotesEight Supplementary Tables and nine Supplementary Figures are available with the online version of this article.

microbiology↗

bioRxiv2023

The seminal odorant binding protein Obp56g is required for mating plug formation and male fertility in Drosophila melanogaster

In Drosophila melanogaster and other insects, the seminal fluid proteins (SFPs) and male sex pheromones that enter the female with sperm during mating are essential for fertility and induce profound post-mating effects on female physiology and behavior. The SFPs in D. melanogaster and other taxa include several members of the large gene family known as odorant binding proteins (Obps). Previous work in Drosophila has shown that some Obp genes are highly expressed in the antennae and can mediate behavioral responses to odorants, potentially by binding and carrying these molecules to odorant receptors. These observations have led to the hypothesis that the seminal Obps might act as molecular carriers for pheromones or other compounds important for male fertility in the ejaculate, though functional evidence in any species is lacking. Here, we used RNAi and CRISPR/Cas9 generated mutants to test the role of the seven seminal Obps in D. melanogaster fertility and the post-mating response (PMR). We found that Obp56g is required for male fertility and the induction of the PMR, whereas the other six genes had no effect on fertility when mutated individually. Obp56g is expressed in the males ejaculatory bulb, an important tissue in the reproductive tract that synthesizes components of the mating plug. We found males lacking Obp56g fail to form a mating plug in the mated females reproductive tract, leading to ejaculate loss and reduced sperm storage. We also examined the evolutionary history of these seminal Obp genes, as several studies have documented rapid evolution and turnover of SFP genes across taxa. We found extensive lability in gene copy number and evidence of positive selection acting on two genes, Obp22a and Obp51a. Comparative RNAseq data from the male reproductive tract of multiple Drosophila species revealed that Obp56g shows high male reproductive tract expression only in species of the melanogaster and obscura groups, though conserved head expression in all species tested. Together, these functional and expression data suggest that Obp56g may have been co-opted for a reproductive function over evolutionary time.

genetics↗

bioRxiv2023

UVB modifies skin immune-stroma cross-talk and promotes effector T cell recruitment during cryptic Leishmania donovani infection

Many parasites of significant public health importance assume skin residency without causing overt pathlogy. How immune and stromal cells respond to such "cryptic" infections and how exposure to UVB alters such responses in poorly understood. We combined scRNA-seq, spatial transcriptomics and inferential network analysis to address these questions in a model of cryptic skin infection by Leishmania donovani. In infected C57BL/6 mice, p-selectin and CXCL12 interactions dominate intercellular communication between leucocytes, fibroblast and endothelial cells, but effector T cell function remains muted. Following UVB exposure, increased numbers of IFN{gamma}+ CD4+ Th1 cells and NK cells enter the skin, communicating with stromal cells via CCL5-CCR5 and LFA-1-ICAM1/2. However, spatial mapping indicated that Th1 cells and macrophages occupied distinct niches after UVB exposure, likely limiting effector function. Our data provide the first holistic view of the immune landscape during cryptic L. donovani infection and demonstrate how UVB exposure fundamentally reshapes this response. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/526940v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1238cbaorg.highwire.dtl.DTLVardef@ec350eorg.highwire.dtl.DTLVardef@18f412corg.highwire.dtl.DTLVardef@1ffd468_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

PointVS: A Machine Learning Scoring Function that Identifies Important Binding Interactions

Over the last few years, many machine learning-based scoring functions for predicting the binding of small molecules to proteins have been developed. Their objective is to approximate the distribution which takes two molecules as input and outputs the energy of their interaction. Only a scoring function that accounts for the interatomic interactions involved in binding can accurately predict binding affinity on unseen molecules. However, many scoring functions make predictions based on dataset biases rather than an understanding of the physics of binding. These scoring functions perform well when tested on similar targets to those in the training set, but fail to generalise to dissimilar targets. To test what a machine learning-based scoring function has learnt, input attribution--a technique for learning which features are important to a model when making a prediction on a particular data point--can be applied. If a model successfully learns something beyond dataset biases, attribution should give insight into the important binding interactions that are taking place. We built a machine learning-based scoring function that aimed to avoid the influence of bias via thorough train and test dataset filtering, and show that it achieves comparable performance on the CASF-2016 benchmark to other leading methods. We then use the CASF-2016 test set to perform attribution, and find that the bonds identified as important by PointVS, unlike those extracted from other scoring functions, have a high correlation with those found by a distance-based interaction profiler. We then show that attribution can be used to extract important binding pharmacophores from a given protein target when supplied with a number of bound structures. We use this information to perform fragment elaboration, and see improvements in docking scores compared to using structural information from a traditional, data-based approach. This not only provides definitive proof that the scoring function has learnt to identify some important binding interactions, but also constitutes the first deep learning-based method for extracting structural information from a target for molecule design.

bioinformatics↗

bioRxiv2022

Laboratory evaluation of a quaternary ammonium compound (QAC)-based antimicrobial coating used in public transport during the COVID-19 pandemic

The virucidal activity of a quaternary ammonium compound (QAC)-based antimicrobial coating used by the UK rail industry during the COVID-19 pandemic was evaluated using the bacteriophage {phi}6 as a surrogate for SARS-CoV-2. Immediately after application and in the absence of interfering substance, the product showed efficacy (>3 log10 reduction) on some materials typically used in rail carriages (stainless steel, high pressure laminate and plastic), variable efficacy on glass and no efficacy (<3 log10 reduction) on a train armrest made of Terluran 22. If, after application of the product, the surfaces remained undisturbed, the antimicrobial coating retained its efficacy for at least 28 days on all materials where it was effective immediately after application. However, regardless of the material coated or time since application, the presence of organic debris (fetal bovine serum) significantly reduced the viricidal activity of the coating. Wiping the surface with a wetted cloth after organic debris deposition was not sufficient to restore efficacy. We conclude that the product is likely to be of limited effectiveness in a busy multi-user environment such as public transport. ImportanceThis study evaluated the performance of a commercially available antimicrobial coating used by the transport industry in the UK during the COVID-19 pandemic. While the product initially showed efficacy against {phi}6 when applied to some materials, when organic debris was subsequently deposited, the efficacy was severely diminished and could not be recovered through wiping (cleaning) the surface. This highlights the importance of including relevant materials and conditions when evaluating antimicrobial coatings in the laboratory. Further efforts are required to identify suitable infection prevention and control practices for the transport industry.

microbiology↗

bioRxiv2022

Higher aboveground carbon stocks in mixed-species planted forests than monocultures - a meta-analysis

Natural forest is declining globally as the area of planted forest increases. Planted forests are often monocultures, despite results suggesting that higher species richness improves ecosystem functioning and stability. To test if this is generally the case, we performed a meta-analysis of available results. We assessed aboveground carbon stocks in mixed-species planted forests vs (a) the average of constituent species monocultures, (b) the best constituent species monoculture, and (c) commercial species monocultures. We investigated whether any advantage of mixtures over monocultures was positively related to species richness, as well as potential mechanisms driving differences in carbon stocks between mixtures and monocultures. The meta-analysis dataset included 79 comparisons from 21 sites. Carbon stocks in mixed planted forests were higher than the average of stocks in monocultures of their constituent species, containing on average 70% more carbon. Mixed planted forests also out-performed commercial monocultures, containing on average 77% more carbon. There was c.25% more carbon in mixed planted forests relative to the best performing monocultures, although this difference was not statistically significant. Overyielding was highest in four-species mixtures (richness range 2-6 species). More data providing better coverage of richness and age gradients (study sites aged 3.5-28 years) is needed to increase confidence in these results. None of the potential mechanisms we examined (nitrogen-fixer present vs absent; native vs non-native/mixed origin; tree diversity experiment vs forestry plantation) consistently explained variation in the diversity effects. This suggests that our findings are driven by a combination of small (statistically insignificant) effects from these sources or further unidentified mechanisms or some combination of the two. We conclude that increasing tree species richness in planted forests can increase carbon stocks while bringing other potential benefits associated with diversification. However, implementation will depend on the balance of these benefits relative to the operational challenges and costs of diversification.

ecology↗

bioRxiv2021

Novel Hendra virus variant detected by sentinel surveillance of Australian horses.

A novel Hendra virus (HeV) variant, not detected by routine testing, was identified and isolated from a Queensland horse that suffered acute, fatal disease consistent with HeV infection. Whole genome sequencing and phylogenetic analysis demonstrated the variant to have ~83% nucleotide identity to the prototype HeV strain. An updated RT-qPCR assay was designed for routine HeV surveillance. In silico and in vitro comparison of the receptor-binding protein with prototypic HeV showed that the human monoclonal antibody m102.4 used for post-exposure prophylaxis, as well as the current equine vaccine, should be effective against this variant. Genetic similarity of this virus to sequences detected from grey-headed flying-foxes suggests the variant circulates at-least in this species. Studies determining infection kinetics, pathogenicity, reservoir-species associations, viral-host co-evolution and spillover dynamics for this virus are urgently needed. Surveillance and biosecurity practices should be updated to appreciate HeV spillover risk across all regions frequented by flying foxes.

molecular biology↗

bioRxiv2021

Spatial point pattern analysis identifies mechanisms shaping the skin parasite landscape in Leishmania donovani infection

Increasing evidence suggests that infectiousness of hosts carrying parasites of the Leishmania donovani complex, the causative agents of visceral leishmaniasis, is linked to parasite repositories in the host skin. However, a detailed understanding of the dispersal and dispersion of these obligatory-intracellular parasites and their host phagocytes in the skin is lacking. Using endogenously fluorescent parasites as a proxy, we apply image analysis combined with spatial point pattern models borrowed from ecology to characterize dispersion of parasitized myeloid cells (including ManR+ and CD11c+ cells) and predict dispersal mechanisms in a previously described immunodeficient model of L. donovani infection. Our results suggest that after initial seeding of infection in the skin, heavily parasite-infected myeloid cells are found in patches that resemble innate granulomas. Spread of parasites from these initial patches subsequently occurs through infection of recruited myeloid cells, ultimately leading to self-propagating networks of patch clusters. This combination of imaging and ecological pattern analysis to identify mechanisms driving the skin parasite landscape offers new perspectives on myeloid cell behavior following parasitism by L. donovani and may also be applicable to elucidating the behavior of other intracellular tissue-resident pathogens and their host cells.

microbiology↗

bioRxiv2021

INfrastructure for a PHAge REference Database: Identification of large-scale biases in the current collection of phage genomes

BackgroundWith advances in sequencing technology and decreasing costs, the number of bacteriophage genomes that have been sequenced has increased markedly in the last decade. Materials and MethodsWe developed an automated retrieval and analysis system for bacteriophage genomes, INPHARED (https://github.com/RyanCook94/inphared), that provides data in a consistent format. ResultsAs of January 2021, 14,244 complete phage genomes have been sequenced. The data set is dominated by phages that infect a small number of bacterial genera, with 75% of phages isolated only on 30 bacterial genera. There is further bias with significantly more lytic phage genomes than temperate within the database, resulting in ~54% of temperate phage genomes originating from just three host genera. Within phage genomes, putative antibiotic resistance genes were found in higher frequencies in temperate phages than lytic phages. ConclusionWe provide a mechanism to reproducibly extract complete phage genomes and highlight some of the biases within this data, that underpins our current understanding of phage genomes.

microbiology↗

bioRxiv2021

Interferon-γ-producing CD4+ T cells drive monocyte activation in the bone marrow during experimental Leishmania donovani infection.

Ly6Chi inflammatory monocytes develop in the bone marrow and migrate to the site of infection during inflammation. Upon recruitment, Ly6Chi monocytes can differentiate into dendritic cells or macrophages. According to the tissue environment they can also acquire different functions. Several studies have described pre-activation of Ly6Chi monocytes in the bone marrow during parasitic infection, but whether this process occurs during experimental visceral leishmaniasis and, if so, the mechanisms contributing to their activation are yet to be established. In wild type C57BL/6 (B6) mice infected with Leishmania donovani, the number of bone marrow Ly6Chi monocytes increased over time. Ly6Chi monocytes displayed a highly activated phenotype from 28 days to 5 months post infection (p.i), with >90% expressing MHCII and >20% expressing iNOS. In comparison, in B6.Rag2-/- mice <10% of bone marrow monocytes were MHCII+ at day 28 p.i., an activation deficiency that was reversed by adoptive transfer of CD4+ T cells. Depletion of CD4+ T cells in B6 mice and the use of mixed bone marrow chimeras further indicated that monocyte activation was driven by IFN-{gamma} produced by CD4+ T cells. In B6.Il10-/- mice, L. donovani infection induced a faster but transient activation of bone marrow monocytes, which correlated with the magnitude of CD4+ T cell production of IFN-{gamma} and resolution of the infection. Under all of the above conditions, monocyte activation was associated with greater control of parasite load in the bone marrow. Through reinfection studies in B6.Il10-/- mice and drug (AmBisome) treatment of B6 mice, we also show the dependence of monocyte activation on parasite load. In summary, these data demonstrate that during L. donovani infection, Ly6Chi monocytes are primed in the bone marrow in a process driven by CD4+ T cells and whereby IFN-{gamma} promotes and IL-10 limits monocyte activation and that the presence of parasites/parasite antigen plays a crucial role in maintaining bone marrow monocyte activation.

immunology↗

bioRxiv2021

On-off transition and ultrafast decay of amino acid luminescence driven by modulation of supramolecular packing

It has been experimentally observed that various biomolecules exhibit clear luminescence in the visible upon aggregation, contrary their monomeric state. However, the physical basis for this phenomenon is still elusive. Here, we systematically examine all coded amino acids to provide non-biased insights into this phenomenon. Several amino acids, including non-aromatic, show intense visible luminescence. While lysine crystals display the highest signal, the very chemically similar non-coded ornithine does not, implying a role for molecular packing rather than the chemical characteristics of the molecule. Furthermore, cysteine show luminescence that is indeed crystal-packing-dependent as repeated rearrangements between two crystal structures result in a reversible on-off optical transition. In addition, ultrafast lifetime decay is experimentally validated, corroborating a recently raised hypothesis regarding the governing role of n{pi}* states in the emission formation. Collectively, our study supports the hypothesis that electronic interactions between molecules that are non-fluorescent and non-absorbing at the monomeric state may result in reversible optically-active states by the formation of supramolecular fluorophores.

biophysics↗

bioRxiv2021

Genomic structure and diversity of oak populations in British Parklands

The two predominant oak species in Britain are Quercus robur (English or pedunculate oak) and Q. petraea (sessile oak). We sequenced the whole genomes of 386 oak trees from four British parkland sites and found over 50 million nuclear single nucleotide polymorphisms (SNPs), allowing us to identify 360 Q. robur, ten Q. petraea and 16 hybrid individuals using clustering methods. Comparing Q. robur and Q. petraea trees from Attingham Park, we found that the nuclear genomes of the two species are largely undifferentiated but identified 81 coding regions exhibiting strong interspecific differentiation. The nuclear genomes of our 360 Q. robur individuals showed no clear differentiation among the four parkland sites. Scans for selective sweeps in Q. robur highlighted regions containing genes with putative involvement in stress tolerance, one of which was moderately differentiated from Q. petraea. Reconstructions of past effective population sizes suggested a long population size decline in both Q. robur and Q. petraea over the Pleistocene, but population growth after the last glacial maximum. We assembled the whole chloroplast genomes of 287 Q. robur, 8 Q. petraea and 14 hybrid trees. In a phylogenetic network, these fell into five major haplotypes, which were shared among species but differed in frequency among parkland sites. We matched our chloroplast genome haplotypes to restriction enzyme fragment haplotypes identified in older studies that had surveyed ancient woodlands in Britain and much of Europe. This suggested that the parkland populations in our study derive from local seed sources.

genomics↗

bioRxiv2020

Analysis of selection methods to develop novel phage therapy cocktails against antimicrobial resistant clinical isolates of bacteria

Antimicrobial resistance (AMR) is a major problem globally. The main bacterial organisms associated with urinary tract infection (UTI) associated sepsis are E. coli and Klebsiella along with Enterobacter species. These all have AMR strains known as ESBL (Extended Spectrum Beta-Lactamase), which are featured on the WHO priority pathogens list as critical for research. Bacteriophages (phages) as viruses that can infect and kill bacteria, could provide an effective tool to tackle these AMR strains. There is currently no gold standard for developing a phage cocktail. Here we describe a novel approach to develop an effective phage cocktail against a set of ESBL-producing E. coli and Klebsiella largely isolated from patients in UK hospitals. By comparing different measures of phage efficacy, we show which are the most robust, and suggest an efficient screening cascade that could be used to develop phage cocktails to target other AMR bacterial species. A target panel of 38 ESBL-producing clinical strains isolated from urine samples was collated and used to test phage efficacy. After an initial screening of 68 phages, six were identified and tested against these 38 strains to determine their clinical coverage and killing efficiency. To achieve this, we assessed four different methods to assess phage virulence across these bacterial isolates. These were the Direct Spot Test (DST), the Efficiency of Plating (EOP) assay, the planktonic killing assay and the biofilm assay. The final ESBL cocktail of six phages could effectively kill 23/38 strains (61%) for Klebsiella 13/19 (68%) and for E. coli 10/19 (53%) based on the planktonic killing assay data. The ESBL E. coli collection had six isolates from the prevalent UTI-associated ST131 sequence type, five of which were targeted effectively by the final cocktail. Of the four methods used to assess phage virulence, the data suggests that planktonic killing assays are as effective as the much more time-consuming EOPs and data for the two assays correlates well. This suggests that planktonic killing is a good proxy to determine which phages should be used in a cocktail. This assay when combined with the virulence index also allows phage synergy to inform cocktail design.

microbiology↗

bioRxiv2020

Dataset Augmentation Allows Deep Learning-Based Virtual Screening To Better Generalise To Unseen Target Classes, And Highlight Important Binding Interactions

Current deep learning methods for structure-based virtual screening take the structures of both the protein and the ligand as input but make little or no use of the protein structure when predicting ligand binding. Here we show how a relatively simple method of dataset augmentation forces such deep learning methods to take into account information from the protein. Models trained in this way are more generalisable (make better predictions on protein-ligand complexes from a different distribution to the training data). They also assign more meaningful importance to the protein and ligand atoms involved in binding. Overall, our results show that dataset augmentation can help deep learning based virtual screening to learn physical interactions rather than dataset biases. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/979625v2_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@609f5forg.highwire.dtl.DTLVardef@17f2cbborg.highwire.dtl.DTLVardef@51e854org.highwire.dtl.DTLVardef@16c111f_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

Protein Targets of Inositol Pyrophosphate (5-IP7) in the parasite Trypanosoma cruzi

Diphosphoinositol-5-pentakisphosphate (5-PP-P5), also known as inositol heptakisphosphate (5-IP7), has been described as a high-energy phosphate metabolite that participates in the regulation of multiple cellular processes through protein binding or serine pyrophosphorylation, a post-translational modification involving a {beta}-phosphoryl transfer. In this study, utilizing an immobilized 5-IP7 affinity reagent, we performed pull-down experiments coupled with mass spectrometry identification, and bioinformatic analysis, to reveal 5-IP7-regulated processes in the two proliferative stages of the unicellular parasite Trypanosoma cruzi. Our protein screen clearly defined two cohorts of putative targets either in the presence of magnesium ions or in metal-free conditions. The highest number of protein targets was detected in the absence of metal ions, with an overrepresentation of proteins involved in purine metabolism, protein phosphorylation, nucleosome assembly, cell redox homeostasis, parasite-surface components, and exocytosis, and only a 37% overlap between the two proliferative stages. In the presence of magnesium, there was a lower enrichment with the isolation of about 30 proteins with overrepresented candidates involved in tRNA amino acylation, phosphate homeostasis, lipid and glucose catabolism, and cell division, and 15% overlap between proliferative stages. To validate the pull-down results, we endogenously tagged four protein candidates and immunopurified them. Among the most interesting targets, we identified a choline/o-acetyltransferase domain-containing phosphoprotein that undergoes 5-IP7-mediated phosphorylation events at a polyserine tract (Ser578-580). We also identified a novel SPX domain-containing phosphoribosyl transferase [EC 2.7.6.1] herein termed as TcPRPS4. Our data revealed new functional roles of 5-IP7 in this divergent eukaryote, and provided potential new targets for chemotherapy.

microbiology↗