Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology.

We present a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS2) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-curation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS1-based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS2 straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-curation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

Plant size, latitude, and phylogeny explain within-population variability in herbivory.

Interactions between plants and herbivores are central in most ecosystems, but their strength is highly variable. The amount of variability within a system is thought to influence most aspects of plant-herbivore biology, from ecological stability to plant defense evolution. Our understanding of what influences variability, however, is limited by sparse data. We collected standardized surveys of herbivory for 503 plant species at 790 sites across 116° of latitude. With these data, we show that within-population variability in herbivory increases with latitude, decreases with plant size, and is phylogenetically structured. Differences in the magnitude of variability are thus central to how plant-herbivore biology varies across macroscale gradients. We argue that increased focus on interaction variability will advance understanding of patterns of life on Earth.

All-in-One Pseudo-MS3 Method for the Analysis of Gas-Phase Cleavable Protein Crosslinking Reactions.

Crosslinking mass spectrometry (XL-MS) supports structure analysis of individual proteins and highly complex whole-cell interactomes. The identification of crosslinked peptides from enzymatic digests remains challenging, especially at the cell level. Empirical methods that use gas-phase cleavable crosslinkers can simplify the identification process by enabling an MS3-based strategy that turns crosslink identification into a simpler problem of detecting two separable peptides. However, the method is limited to select instrument platforms and is challenged by duty cycle constraints. Here, we revisit a pseudo-MS3 concept that incorporates in-source fragmentation, where a fast switch between gentle high-transmission source conditions and harsher in-source fragmentation settings liberates peptides for standard MS2-based peptide identification. We present an all-in-one method where retention time matches between the crosslink precursor and the liberated peptides establish linkage, and MS2 sequencing identifies the source-liberated peptides. We demonstrate that DC4, a very labile cleavable crosslinker, generates high-intensity peptides in-source. Crosslinks can be identified from these liberated peptides, as they are chromatographically well-resolved from monolinks. Using bovine serum albumin (BSA) as a crosslinking test case, we detect 27% more crosslinks with pseudo-MS3 over a best-in-class MS3 method. While performance is slightly lower for whole-cell lysates (generating two-thirds of the identifications of a standard method), we find that 60% of these hits are unique, highlighting the complementarity of the method.

High-Sensitivity Proteome-Scale Searches for Crosslinked Peptides Using CRIMP 2.0.

Crosslinking mass spectrometry (XL-MS) is a valuable technique for generating point-to-point distance measurements in protein space. However, cell-based XL-MS experiments require efficient software that can detect crosslinked peptides with sensitivity and controlled error rates. Many algorithms implement a filtering strategy designed to reduce the size of the database prior to mounting a search for crosslinks, but concern has been expressed over the possibility of reduced sensitivity using these strategies. We present a new scoring method that uses a rapid presearch method and a concept inspired by computer vision algorithms to resolve crosslinks from other conflicting reaction products. Searches of several curated crosslink datasets demonstrate high crosslink detection rates, and even the most complex proteome-level searches (using cleavable or noncleavable crosslinkers) can be completed efficiently on a conventional desktop computer. The detection of protein-protein interactions is increased twofold through the inclusion of compositional terms in the scoring equation. The combined functionality is made available as CRIMP 2.0 in the Mass Spec Studio.

Doublecortin engages the microtubule lattice through a cooperative binding mode involving its C-terminal domain.

Doublecortin (DCX) is a microtubule (MT)-associated protein that regulates MT structure and function during neuronal development and mutations in DCX lead to a spectrum of neurological disorders. The structural properties of MT-bound DCX that explain these disorders are incompletely determined. Here, we describe the molecular architecture of the DCX-MT complex through an integrative modeling approach that combines data from X-ray crystallography, cryo-electron microscopy, and a high-fidelity chemical crosslinking method. We demonstrate that DCX interacts with MTs through its N-terminal domain and induces a lattice-dependent self-association involving the C-terminal structured domain and its disordered tail, in a conformation that favors an open, domain-swapped state. The networked state can accommodate multiple different attachment points on the MT lattice, all of which orient the C-terminal tails away from the lattice. As numerous disease mutations cluster in the C-terminus, and regulatory phosphorylations cluster in its tail, our study shows that lattice-driven self-assembly is an important property of DCX.

IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics.

Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.

Improving Spectral Validation Rates in Hydrogen-Deuterium Exchange Data Analysis.

The data analysis practices associated with hydrogen-deuterium exchange mass spectrometry (HX-MS) lag far behind that of most other MS-based protein analysis tools. A reliance on external tools from other fields and a persistent need for manual data validation restrict this powerful technology to the expert user. Here, we provide an extensive upgrade to the HX data analysis suite available in the Mass Spec Studio in the form of two new apps (HX-PIPE and HX-DEAL), completing a workflow that provides an HX-tailored peptide identification capability, accelerated validation routines, automated spectral deconvolution strategies, and a rich set of exportable graphics and statistical reports. With these new tools, we demonstrate that the peptide identifications obtained from undeuterated samples generated at the start of a project contain information that helps predict and control the extent of manual validation required. We also uncover a large fraction of HX-usable peptides that remains unidentified in most experiments. We show that automated spectral deconvolution routines can identify exchange regimes in a project-wide manner, although they remain difficult to accurately assign in all scenarios. Taken together, these new tools provide a robust and complete solution suitable for the analysis of high-complexity HX-MS data.

Harmonizing structural mass spectrometry analyses in the mass spec studio.

Structural Mass Spectrometry (SMS) provides a comprehensive toolbox for the analysis of protein structure and function. It offers multiple sources of structural information that are increasingly useful for integrative structural modeling of complex protein systems. As MS-based structural workflows scale to larger systems, consistent and coherent data interpretation resources are needed to better support modeling. Unlike the proteomics community, practitioners of SMS lack adequate computational tools. Here, we review new developments in the Mass Spec Studio: an expandable ecosystem of workflows for the analysis of complementary SMS techniques with linkages to modeling. Current functionality in the Studio (version 2) supports three major SMS workflows (crosslinking, hydrogen/deuterium exchange and covalent labelling) and two pipelines for structural modeling, with a special focus on data integration. The Mass Spec Studio is an architecture focused on rapid and robust extension of functionality by a community of developers. SIGNIFICANCE: This review surveys the new data analysis capabilities within the Mass Spec Studio, a rich framework for rapid software development specifically targeting the community of structural proteomics and structural mass spectrometry. Updates to crosslinking, hydrogen/deuterium-exchange and covalent labeling apps are provided as well as a utility for translating such analyses into restraints that support integrative structural modeling. These new capabilities, together with the underlying design tools and content, provide the community with a wealth of resources to tackle complex structural problem and design new approaches to data analysis.

The Oxylipin Signaling Pathway Is Required for Increased Aphid Attraction and Retention on Virus-Infected Plants.

Many studies have shown that virus infection alters phytohormone signaling and insect vector contact with hosts. Increased vector contact and movement among plants should increase virus survival and host range. In this study we examine the role of virus-induced changes in phytohormone signaling in plant-aphid interactions, using Pea enation mosaic virus (PEMV), pea aphids (Acyrthosiphon pisum), and pea (Pisum sativum) as a model. We observed that feeding by aphids carrying PEMV increases salicylic acid and jasmonic acid accumulation in pea plants compared to feeding by virus-free aphids. To determine if induction of the oxylipin jasmonic acid is critical for aphid settling, attraction, and retention on PEMV-infected plants, we conducted insect bioassays using virus-induced gene silencing (VIGS), an oxylipin signaling inducer, methyl jasmonate (MeJA), and a chemical inhibitor of oxylipin signaling, phenidone. Surprisingly, there was no impact of phenidone treatment on jasmonic acid or salicylic acid levels in virus-infected plants, though aphid attraction and retention were altered. These results suggest that the observed impacts of phenidone on aphid attraction to and retention on PEMV-infected plants are independent of the jasmonic acid and salicylic acid pathway but may be mediated by another component of the oxylipin signaling pathway. These results shed light on the complexity of viral manipulation of phytohormone signaling and vector-plant interactions.

Plant Water Stress Affects Interactions Between an Invasive and a Naturalized Aphid Species on Cereal Crops.

In cereal cropping systems of the Pacific Northwestern United States (PNW), climate change is projected to increase the frequency of drought during summer months, which could increase water stress for crop plants. Yet, it remains uncertain how interactions between herbivore species are affected by drought stress. Here, interactions between two cereal aphids present in PNW cereal systems, Metopolophium festucae (Theobald) subsp. cerealium (a newly invasive species) and Rhopalosiphum padi L. (a naturalized species), were tested relative to wheat water stress. When aphids were confined in leaf cages on wheat, asymmetrical facilitation occurred; per capita fecundity of R. padi was increased by 46% when M. festucae cerealium was also present, compared to when only R. padi was present. Imposed water stress did not influence this interaction. When aphids were confined on whole wheat plants, asymmetrical competition occurred; cocolonization inhibited M. festucae cerealium population growth but did not affect R. padi population growth. Under conditions of plant water stress, however, the inhibitory effect of R. padi on M. festucae cerealium was not observed. We conclude that beneficial effects of cocolonization on R. padi are due to a localized plant response to M. festucae cerealium feeding, and that cocolonization of plants is likely to suppress M. festucae cerealium populations under ample water conditions, but not when plants are water stressed. This suggests that plant responses to water stress alter the outcome of competition between herbivore species, with implications for the structure of pest communities on wheat during periods of drought.

Fifteen-year trends and predictors of preparation for pregnancy in women with pre-conception Type 1 and Type 2 diabetes: a population-based cohort study.

AIMS: To investigate trends in indicators of preparation for pregnancy in women with Type 1 and Type 2 diabetes and explore their predictors. METHODS: Data on 2293 pregnancies delivered during 1996-2010 by women with Type 1 (n = 1753) and Type 2 (n = 540) diabetes were obtained from the Northern Diabetes in Pregnancy Survey. Multiple logistic regression was used to analyse the relationship between potential predictors and three indicators of inadequate pregnancy preparation: non-attendance for pre-conception care; no pre-conception folate consumption; and peri-conception HbA(1c) ≥ 53 mmol/mol (≥ 7%). RESULTS: Overall, 40.3% of women with diabetes attended pre-conception care, 37.4% reported pre-conception folate consumption, and 28.2% had adequate peri-conception HbA1c . For all patients, pre-conception folate consumption improved over time, while peri-conception glucose control did not. Attendance for pre-conception care for women with Type 1 diabetes significantly declined. Residence in deprived areas, smoking and younger maternal age (for women aged < 35 years) were independently associated with all three indicators of inadequate preparation for pregnancy. Additional predictors of inadequate peri-conception HbA(1c) were: Type 1 diabetes (adjusted odds ratio 5.51, 95% CI 2.71-11.22), longer diabetes history (adjusted odds ratio 1.16, 95% CI 1.09-1.23 per year increase for those with < 15 years' diabetes duration), non-white ethnicity (adjusted odds ratio 3.13, 95% CI 1.23-7.97) and higher BMI (adjusted odds ratio 1.05, 95% CI 1.01-1.09 per 1-kg/m(2) increase). Non-attendance for pre-conception care was additionally associated with Type 2 diabetes (P = 0.003) and multiparity (P < 0.0001). CONCLUSIONS: There are socio-demographic inequalities in preparation for pregnancy among women with diabetes. Women with Type 2 diabetes were less likely to attend pre-conception care. Pre-conception services need to be designed to maximize uptake in all groups.

Universal screening to identify gestational diabetes: a multi-centre study in the North of England.

We conducted an audit of treatment and outcomes in 116 women with gestational diabetes. These women received intense monitoring and high levels of medical and obstetric intervention. 24% would not have been identified by risk factor based screening. Cost effective strategies to identify all women with gestational diabetes are needed.

Roles of mating behavioural interactions and life history traits in the competition between alien and indigenous whiteflies.

Interference competition between closely related alien and indigenous species often influences the outcome of biological invasions. The whitefly Bemisia tabaci species complex contains ≥28 putative species and two of them, Mediterranean (MED, formally referred to as the 'Q biotype') and Middle East-Asia Minor 1 (MEAM1, formally referred to as the 'B biotype'), have recently spread to much of the world. In many invaded regions, these species have displaced closely related indigenous whitefly species. In this study, we integrated laboratory population experiments, behavioural observations and simulation modelling to investigate the capacity of MED to displace Asia II 1 (AII1, formally referred to as the 'ZHJ2 biotype'), an indigenous whitefly widely distributed in Asia. Our results show that intensive mating interactions occur between MED and AII1, leading to reduced fecundity and progeny female ratio in AII1, as well as an increase in progeny female ratio in MED. In turn, our population cage experiments demonstrated that MED has the capacity to displace AII1 in a few generations. Using simulation models, we then show that both asymmetric mating interactions and differences in life history traits between the two species contribute substantially to the process of displacement. These findings would help explain the displacement of AII1 by MED in the field and, together with earlier studies on mating interactions between other species of the B. tabaci complex, indicate the widespread significance of asymmetric mating interactions in whitefly species exclusions.

Analyzing haplodiploid inheritance of insecticide resistance in whitefly biotypes.

We developed new methods for analyzing inheritance of insecticide resistance in haplodiploid arthropods and applied them to elucidate resistance of the whitefly Bemisia tabaci (Gennadius) to an insect growth regulator, pyriproxyfen. Two invasive biotypes of this devastating crop pest, the B biotype in Arizona and the Q biotype in Israel, have evolved resistance to pyriproxyfen. Here, we incorporated data from laboratory bioassays and crossing procedures exploiting haplodiploidy into statistical and analytical models to estimate the number of loci affecting pyriproxyfen resistance in strains of both biotypes. In tests with models of one to ten loci, the best fit between expected and observed mortality occurred with a two-locus model for the B biotype strain (QC-02) and for one- and two-locus models for the Q biotype strain (Pyri-R). The estimated minimum number of loci affecting resistance was 1.6 for the B biotype strain and 1.0 for the Q biotype strain. The methods used here can be applied to insecticide resistance and other traits in haplodiploid arthropods.

Economic analysis of dynamic management strategies utilizing. Transgenic corn for control of western corn rootworm (Coleoptera: Chrysomelidae).

We studied management strategies for western corn rootworm, Diabrotica virgifera virgifera LeConte, using transgenic corn, Zea mays L., from both a biological and an economic perspective. In areas with and without populations adapted to a 2-yr rotation of corn and soybean (rotation-resistant), the standard management strategy was to plant 80% of a cornfield (rotated and continuous) to a transgenic cultivar each year. In each area, we also studied dynamic management strategies where the proportion of transgenic corn increased over time in a region. We also analyzed management strategies for a single field that is the first to adopt transgenic corn within a larger unmanaged region. In all areas, increasing the expression of the toxin in the plant increased economic returns. In areas without rotation-resistance, planting 80% transgenic corn in the continuous cornfield each year generated the greatest returns with a medium toxin dose or greater. In areas with alleles for rotation-resistance at low initial levels, a 2-yr rotation of nontransgenic corn and soybean, Glycine max (L.) Merr., may be the most economical strategy if resistance to crop rotation is recessive. If resistance to crop rotation is additive or dominant, planting transgenic corn in the rotated cornfield was the most effective strategy. In areas where rotation-resistance is already a severe problem, planting transgenic corn in the rotated cornfield each year was always the most economical strategy. In some cases the strategies that increased the proportion of transgenic corn in the region over time increased returns compared with the standard strategies. With these strategies the evolution of resistance to crop rotation occurred more rapidly but resistance to transgenic corn was delayed compared with the standard management strategy. In areas not managed by a regional norm, increasing the proportion of transgenic corn and increasing toxin dose in the managed field generally increased returns. In a sensitivity analysis, among the parameters investigated, only density-dependent survival affected the results.

Using a generational time-step model to simulate dynamics of adaptation to transgenic corn and crop rotation by western corn rootworm (Coleoptera: Chrysomelidae).

We expanded a simulation model of the population dynamics and genetics of the western corn rootworm for a landscape of corn, soybean, and other crops to study the simultaneous development of resistance to both crop rotation and transgenic corn. Transgenic corn effective against corn rootworm was recently approved in 2003 and may be a very effective new technology for control of western corn rootworm in areas with or without the rotation-resistant variant. In simulations of areas with rotation-resistant populations, planting transgenic corn to only rotated cornfields was a robust strategy to prevent resistance to both traits. In these areas, planting transgenic corn to only continuous fields was not an effective strategy for preventing adaptation to crop rotation or transgenic corn. In areas without rotation-resistant phenotypes, gene expression of the allele for resistance to transgenic corn was the most important factor affecting the development of resistance to transgenic corn. If the allele for resistance to transgenic corn is recessive, resistance can be delayed longer than 15 yr, but if the resistant allele is dominant then resistance usually developed within 15 yr. In a sensitivity analysis, among the parameters investigated, initial allele frequency and density dependence were the two most important factors affecting the evolution of resistance. We compared the results of this simulation model with a more complicated model and results between the two were similar. This indicates that results from a simpler model with a generational time-step can compare favorably with a more complex model with a daily time-step.

Analysis of the dynamics of adaptation to transgenic corn and crop rotation by western corn rootworm (Coleoptera: Chrysomelidae) using a daily time-step model.

Western corn rootworm, Diabrotica virgifera virgifera LeConte, has overcome crop rotation in several areas of the north central United States. The effectiveness of crop rotation for management of corn rootworm has begun to fail in many areas of the midwestern United States, thus new management strategies need to be developed to control rotation-resistant populations. Transgenic corn, Zea mays L., effective against western corn rootworm, may be the most effective new technology for control of this pest in areas with or without populations adapted to crop rotation. We expanded a simulation model of the population dynamics and genetics of the western corn rootworm for a landscape of corn; soybean, Glycine max (L.); and other crops to study the simultaneous development of resistance to both crop rotation and transgenic corn. Results indicate that planting transgenic corn to first-year cornfields is a robust strategy to prevent resistance to both crop rotation and transgenic corn in areas where rotation-resistant populations are currently a problem or may be a problem in the future. In these areas, planting transgenic corn only in continuous cornfields is not an effective strategy to prevent resistance to either trait. In areas without rotation-resistant populations, gene expression of the allele for resistance to transgenic corn, R, is the most important factor affecting the evolution of resistance. If R is recessive, resistance can be delayed longer than 15 yr. If R is dominant, resistance may be difficult to prevent. In a sensitivity analysis, results indicate that density dependence, rotational level in the landscape, and initial allele frequency are the three most important factors affecting the results.

Economics versus alleles: balancing integrated pest management and insect resistance management for rotation-resistant western corn rootworm (Coleoptera: Chrysomelidae).

Western corn rootworm, Diabrotica virgifera virgifera LeConte, has overcome crop rotation in several areas of the central United States. We expanded a simple model of adult behavior and population genetics to explain how rotation resistance may have developed and to study ways to manage the western corn rootworm in a landscape of corn, soybean, and winter wheat where evolution of resistance may occur. We modeled six alternative management strategies over a 15-yr time horizon, as well as a strategy involving a 2-yr rotation of corn and soybean in 85% of the landscape, to investigate their effectiveness from both a biological and economic perspective. Generally, resistance to crop rotation evolves in fewer than 15 yr, and the rate of evolution increases as the level of rotated landscape (selection pressure) increases. When resistance is recessive, all six alternative strategies were effective at preventing evolution of rotation resistance. The two most successful strategies were the use of transgenic rotated corn in a 2-yr rotation and a 3-yr rotation of corn, soybean, and wheat with unattractive wheat (for oviposition) preceding corn. Results were most sensitive to increases in the initial allele frequency and modifications of the density-dependent survival function. Economically, three alternative strategies were robust solutions to the problem, if technology fees were not too high. Repellant soybean, attractive rotated corn, and transgenic rotated corn, all in 2-yr rotations, were economically valuable approaches. However, even the currently common 2-yr rotation was economical when resistance was recessive and the actual costs of resistance would not be paid until far in the future.