Suereta Fortuin

Background: Tuberculosis (TB) preventive treatment (TPT) is a core component of TB control. Levofloxacin was recently recommended by the World Health Organization as TPT in children exposed to multidrug-resistant tuberculosis (MDR-TB). However, the affordability and feasibility of TPT provision for governments, health services, individual households and global donors is uncertain. Methods: This costing analysis used empirical data collected alongside the TB-CHAMP clinical trial which investigated levofloxacin TPT in children exposed to MDR-TB in South Africa. We modelled the societal (health system and household) cost of levofloxacin TPT, other potential future (but not currently recommended) MDR-TB exposure TPT options and compared with drug-susceptible TPT options in children and adolescents under 15 years old. We modelled costs across 12 different medicine and formulation options for 11 paediatric dosing weight-bands using TB-CHAMP and household survey data, with national and international procurement medicine pricing. Results: Total societal costs of providing levofloxacin TPT and its monitoring per child were US$252 (0- < 5 years) and US$256 (5- < 15-years) and had comparable costs to drug-susceptible TPT regimens when using Global Drug Facility pricing. Pharmaceutical costs for a course of TPT using child-friendly formulations in children <5 years varied between US$38 (levofloxacin), US$80 (bedaquiline) and US$582 (delamanid). Household costs associated with accessing TPT and ongoing monitoring ranged from 1.6%−2.1% of median annual income of affected households, with shorter TPT courses incurring lower household costs. Global Drug Facility procurement achieved TPT pricing at 70% of the costs of national South African procurement, and enabled access to a wider range of child-friendly formulations. Discussion: Costs of TPT are influenced by factors including medicine pricing and procurement, the use of child-friendly formulations, implementation approach, the duration of treatment, and choice of TPT regimen across weight and age distributions. Costs to households are relatively small but may be significant for impoverished households already managing the financial disruption of a family member with MDR-TB disease.

Background: Tuberculosis (TB) preventive treatment (TPT) is a core component of TB control. Levofloxacin was recently recommended by the World Health Organization as TPT in children exposed to multidrug-resistant tuberculosis (MDR-TB). However, the affordability and feasibility of TPT provision for governments, health services, individual households and global donors is uncertain. Methods: TB-CHAMP was a cluster-randomized, double-blind, placebo-controlled trial investigating levofloxacin TPT in children exposed to MDR-TB in South Africa and included cost analysis of TPT delivery. We modelled the societal (health system and household) cost of levofloxacin TPT, other potential future (but not currently recommended) MDR-TB exposure TPT options, and compared with drug-susceptible TPT options in children and adolescents under 15 years old. We modelled costs across 12 different medicine and formulation options for 11 paediatric dosing weight-bands using TB-CHAMP and household survey data, with national and international procurement medicine pricing. Results: Total societal costs of providing levofloxacin TPT and its monitoring per child were US$252 (0-<5-years) and US$256 (5-<15-years) and had comparable costs to drug-susceptible TPT regimens when using Global Drug Facility pricing. Pharmaceutical costs for a course of TPT using paediatric formulations in children <5 years varied between US$38 (levofloxacin), US$80 (bedaquiline) and US$582 (delamanid). Household costs associated with accessing TPT and ongoing monitoring ranged from 1.6%-2.1% of median annual income of affected households, with shorter TPT courses incurring lower household costs. Global Drug Facility procurement achieved TPT pricing at 70% of the costs of national South African procurement, and enabled access to a wider range of child-friendly formulations. Discussion: Costs of TPT are influenced by factors including medicine pricing and procurement, the use of child-friendly formulations, implementation approach, the duration of treatment, and choice of TPT regimen across children’s weight and age distributions. Costs to households are relatively small but may be significant for impoverished households already managing the financial disruption of a family member with MDR-TB disease

Background: Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. Results: We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database—but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. Conclusions: By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.

In proteomics, peptide information within mass spectrometry (MS) data from a specific organism sample is routinely matched against a protein sequence database that best represent such organism. However, if the species/strain in the sample is unknown or genetically poorly characterized, it becomes challenging to determine a database which can represent such sample. Building customized protein sequence databases merging multiple strains for a given species has become a strategy to overcome such restrictions. However, as more genetic information is publicly available and interesting genetic features such as the existence of pan- and core genes within a species are revealed, we questioned how efficient such merging strategies are to report relevant information. To test this assumption, we constructed databases containing conserved and unique sequences for 10 different species. Features that are relevant for probabilistic-based protein identification by proteomics were then monitored. As expected, increase in database complexity correlates with pangenomic complexity. However, Mycobacterium tuberculosis and Bordetella pertussis generated very complex databases even having low pangenomic complexity. We further tested database performance by using MS data from eight clinical strains from M. tuberculosis, and from two published datasets from Staphylococcus aureus. We show that by using an approach where database size is controlled by removing repeated identical tryptic sequences across strains/species, computational time can be reduced drastically as database complexity increases.

Reversible protein phosphorylation, regulated by protein kinases and phosphatases, mediates a switch between protein activity and cellular pathways that contribute to a large number of cellular processes. The Mycobacterium tuberculosis genome encodes 11 Serine/Threonine kinases (STPKs) which show close homology to eukaryotic kinases. This study aimed to elucidate the phosphoproteomic landscape of a clinical isolate of M. tuberculosis. We performed a high throughput mass spectrometric analysis of proteins extracted from an early-logarithmic phase culture. Whole cell lysate proteins were processed using the filter-aided sample preparation method, followed by phosphopeptide enrichment of tryptic peptides by strong cation exchange (SCX) and Titanium dioxide (TiO2) chromatography. The MaxQuant quantitative proteomics software package was used for protein identification. Our analysis identified 414 serine/threonine/tyrosine phosphorylated sites, with a distribution of S/T/Y sites; 38% on serine, 59% on threonine and 3% on tyrosine; present on 303 unique peptides mapping to 214 M. tuberculosis proteins. Only forty five of the S/T/Y phosphorylated proteins identified in our study had been previously described in the laboratory strain H37Rv, confirming previous reports. The remaining 169 phosphorylated proteins were newly identified in this clinical M. tuberculosis Beijing strain. We identified 5 novel tyrosine phosphorylated proteins. These findings not only expand upon our current understanding of the protein phosphorylation network in clinical M. tuberculosis but the data set also further extends and complements previous knowledge regarding phosphorylated peptides and phosphorylation sites in M. tuberculosis.