Extensive public health initiatives drive the elimination of Aedes aegypti (Diptera, Culicidae) from a town in regional Queensland: A case study from Gin Gin, Australia.

Aedes aegypti is the primary vector of exotic arboviruses (dengue, chikungunya and Zika) in Australia. Once established across much of Australia, this mosquito species remains prevalent in central and northern Queensland. In 2011, Ae. aegypti was re-discovered in the town of Gin Gin, Queensland, by health authorities during routine larval surveillance. This town is situated on a major highway that provides a distribution pathway into the highly vulnerable and populous region of the state where the species was once common. Following the detection, larval habitat and adult control activities were conducted as a public health intervention to eliminate the Ae. aegypti population and reduce the risk of exotic disease transmission. Importantly, genetic analysis revealed a homogenous cluster and small effective population vulnerable to an elimination strategy. By 2015, adult surveillance revealed the population had expanded throughout the centre of the town. In response, a collaboration between research agencies and local stakeholders activated a second control program in 2016 that included extensive community engagement, enhanced entomologic surveillance and vector control activities including the targeting of key containers, such as unsealed rainwater tanks. Here we describe a model of the public health intervention which successfully reduced the Ae. aegypti population below detection thresholds, using source reduction, insecticides and novel, intensive genetic surveillance methods. This outcome has important implications for future elimination work in small towns in regions sub-optimal for Ae. aegypti presence and reinforces the longstanding benefits of a partnership model for public health-based interventions for invasive urban mosquito species.

Evidence for co-translational misincorporation of non-canonical amino acid hydroxyproline in recombinant antibodies produced in Chinese Hamster Ovary (CHO) cell lines.

With the advent of highly sensitive technologies such as tandem mass spectrometry and next-generation sequencing, recombinant antibodies are now routinely analyzed for the presence of low-level sequence variants including amino acid misincorporations. During mAb cell culture process development, we found that proline was replaced with the non-canonical amino acid, hydroxyproline, in the protein sequence. We investigated the relationship between proline content in the cell culture media and proline sequence variants and found that the proline concentration was inversely correlated with the amount of sequence variants detected in the protein sequence. Hydroxyproline incorporation has been previously reported in recombinant proteins produced in mammalian expression systems as a post-translational modification. Given the dependency on proline levels, the mechanism was then investigated. To address the possibility of co-translational misincorporation of hydroxyproline, we used tandem mass spectrometry to measure incorporation of stable-isotope labelled hydroxyproline added to the feed of a production bioreactor. We discovered co-translational misincorporation of labelled hydroxyproline in the recombinant antibody. These findings are significant, since they underscore the need to track non-canonical amino acid incorporation as a co-translational event in CHO cells. Understanding the mechanism of hydroxyproline incorporation is crucial in developing an appropriate control strategy during biologics production.

Assessing Protein Sequence Database Suitability Using De Novo Sequencing.

The analysis of samples from unsequenced and/or understudied species as well as samples where the proteome is derived from multiple organisms poses two key questions. The first is whether the proteomic data obtained from an unusual sample type even contains peptide tandem mass spectra. The second question is whether an appropriate protein sequence database is available for proteomic searches. We describe the use of automated de novo sequencing for evaluating both the quality of a collection of tandem mass spectra and the suitability of a given protein sequence database for searching that data. Applications of this method include the proteome analysis of closely related species, metaproteomics, and proteomics of extinct organisms.

Accurate de novo design of hyperstable constrained peptides.

Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for accurate de novo design of conformationally restricted peptides, and the use of these methods to design 18-47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N-C backbone-cyclized. Both genetically encodable and non-canonical peptides are exceptionally stable to thermal and chemical denaturation, and 12 experimentally determined X-ray and NMR structures are nearly identical to the computational design models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs.

De novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificity.

In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.

SILAC surrogates: rescue of quantitative information for orphan analytes in spike-in SILAC experiments.

Super-stable isotope labeling by amino acids in cell culture (Super-SILAC) enables the sensitive and accurate analysis of complex biological tissue and tumor samples by comparison of light peptides observed in biological samples to heavy peptides from SILAC cell culture spike-ins. However, despite the use of multiple cell lines for Super-SILAC spike-in standards, the full protein and peptide profiles of biological samples are not completely represented in these internal standards, leading to orphan analytes for which sample to standard ratios cannot be calculated. This problem is exacerbated in some biological systems, such as muscle tissue, which lack adequate cell culture lines to reflect their complex and idiosyncratic protein profiles, resulting in up to 40% of peptide analytes without heavy cognates. Furthermore, these unquantified orphan analytes may be among the most biologically interesting and significant species, since their presence is not common to cell lines cultured in vitro. Here, we report on the development of a surrogate analysis strategy to interpolate quantitative relationships between peptide species, observed across multiple biological samples, which lack representation within the spike-in standards. The precision and accuracy of this method was assessed by replicate experiments in which surrogate-derived ratios from defined mixtures of spike-in SILAC standard and tissue lysate were compared against traditional SILAC ratios for species where both light and heavy peptide cognates were observed. We demonstrate the robustness of our SILAC surrogates strategy across a variety of murine tissues, including liver, spleen, brain, and muscle. Our approach increases the quantitative coverage and precision within a biological sample by rescuing previously intractable peptide species and applying additional evidence to improve the precision of existing quantifications.

Increasing phosphoproteomic coverage through sequential digestion by complementary proteases.

Protein phosphorylation is a reversible post-translational modification known to regulate protein function, subcellular localization, complex formation, and protein degradation. Detailed phosphoproteomic information is critical to kinomic studies of signal transduction and for elucidation of cancer biomarkers, such as in non-small-cell lung adenocarcinoma, where phosphorylation is commonly dysregulated. However, the collection and analysis of phosphorylation data remains a difficult problem. The low concentrations of phosphopeptides in complex biological mixtures as well as challenges inherent in their chemical nature have limited phosphoproteomic characterization and some phosphorylation sites are inaccessible by traditional workflows. We developed a sequential digestion method using complementary proteases, Glu-C and trypsin, to increase phosphoproteomic coverage and supplement traditional approaches. The sequential digestion method is more productive than workflows utilizing only Glu-C and we evaluated the orthogonality of the sequential digestion method relative to replicate trypsin-based analyses. Finally, we demonstrate the ability of the sequential digestion method to access new regions of the phosphoproteome by comparison to existing public phosphoproteomic databases. Our approach increases coverage of the human lung cancer phosphoproteome by accessing both new phosphoproteins and novel phosphorylation site information.

Statistical estimates of absenteeism attributable to seasonal and pandemic influenza from the Canadian Labour Force Survey.

BACKGROUND: As many respiratory viruses are responsible for influenza like symptoms, accurate measures of the disease burden are not available and estimates are generally based on statistical methods. The objective of this study was to estimate absenteeism rates and hours lost due to seasonal influenza and compare these estimates with estimates of absenteeism attributable to the two H1N1 pandemic waves that occurred in 2009. METHODS: Key absenteeism variables were extracted from Statistics Canada's monthly labour force survey (LFS). Absenteeism and the proportion of hours lost due to own illness or disability were modelled as a function of trend, seasonality and proxy variables for influenza activity from 1998 to 2009. RESULTS: Hours lost due to the H1N1/09 pandemic strain were elevated compared to seasonal influenza, accounting for a loss of 0.2% of potential hours worked annually. In comparison, an estimated 0.08% of hours worked annually were lost due to seasonal influenza illnesses. Absenteeism rates due to influenza were estimated at 12% per year for seasonal influenza over the 1997/98 to 2008/09 seasons, and 13% for the two H1N1/09 pandemic waves. Employees who took time off due to a seasonal influenza infection took an average of 14 hours off. For the pandemic strain, the average absence was 25 hours. CONCLUSIONS: This study confirms that absenteeism due to seasonal influenza has typically ranged from 5% to 20%, with higher rates associated with multiple circulating strains. Absenteeism rates for the 2009 pandemic were similar to those occurring for seasonal influenza. Employees took more time off due to the pandemic strain than was typical for seasonal influenza.

An analysis pipeline for the inference of protein-protein interaction networks.

We present a platform for the reconstruction of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey data. The Software Environment for Biological Network Inference (SEBINI), an environment for the deployment of network inference algorithms that use high-throughput data, forms the platform core. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data. Also, the pipeline incorporates the Collective Analysis of Biological Interaction Networks (CABIN) software. We have thus created a structured workflow for protein-protein network inference and supplemental analysis.

Diabetes-prevalence and care practices.

In 2005, an estimated 1.3 million Canadians aged 12 or older (4.9% of the population of these ages) reported to the Canadian Community Health Survey (CCHS) that they had been diagnosed with diabetes. The Canadian Diabetes Association has published Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada,which recommend the type of care that should be provided to individuals with diabetes. According to the CCHS, and based on data from six of the provinces/territories (Newfoundland and Labrador, Prince Edward Island, New Brunswick, Ontario, Manitoba and Yukon Territory), almost three-quarters of diabetic respondents aged 18 or older reported having had their hemoglobin A1C checked by a health care professional at least once in the year before the survey, and those who had had the test were close to meeting the recommended frequency of every three months. The majority of diabetic respondents were also meeting the recommendation for eye examinations, but only half had the recommended annual foot examinations. Half the diabetic population reported that they or a family member had checked their glucose level every day.

A general system for studying protein-protein interactions in Gram-negative bacteria.

One of the most promising methods for large-scale studies of protein interactions is isolation of an affinity-tagged protein with its in vivo interaction partners, followed by mass spectrometric identification of the copurified proteins. Previous studies have generated affinity-tagged proteins using genetic tools or cloning systems that are specific to a particular organism. To enable protein-protein interaction studies across a wider range of Gram-negative bacteria, we have developed a methodology based on expression of affinity-tagged "bait" proteins from a medium copy-number plasmid. This construct is based on a broad-host-range vector backbone (pBBR1MCS5). The vector has been modified to incorporate the Gateway DEST vector recombination region, to facilitate cloning and expression of fusion proteins bearing a variety of affinity, fluorescent, or other tags. We demonstrate this methodology by characterizing interactions among subunits of the DNA-dependent RNA polymerase complex in two metabolically versatile Gram-negative microbial species of environmental interest, Rhodopseudomonas palustris CGA010 and Shewanella oneidensis MR-1. Results compared favorably with those for both plasmid and chromosomally encoded affinity-tagged fusion proteins expressed in a model organism, Escherichia coli.

A Bayesian estimator of protein-protein association probabilities.

UNLABELLED: The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro aff3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein liquid chromatography tandem mass spectrometry LC-MS/MS affinity isolation experiments. AVAILABILITY: BEPro (3) is public domain software, has been tested on WIndows XP, Linux and Mac OS, and is freely available from http://www.pnl.gov/statistics/BEPro3. SUPPLEMENTARY INFORMATION: A user guide, example dataset with analysis and additional documentation are included with the BEPro (3) download.