Dynamic role of personality in explaining COVID-19 vaccine hesitancy and refusal.

Vaccine hesitancy and refusal are threats to sufficient response to the COVID-19 pandemic and public health efforts more broadly. We focus on personal characteristics, specifically personality, to explain what types of people are resistant to COVID-19 vaccination and how the influence of these traits changed as circumstances surrounding the COVID-19 pandemic evolved. We use a large survey of over 40,000 Canadians between November 2020 and July 2021 to examine the relationship between personality and vaccine hesitancy and refusal. We find that all five facets of the Big-5 (openness to experience, conscientiousness, extraversion, agreeableness, and negative emotionality) are associated with COVID-19 vaccine refusal. Three facets (agreeableness, conscientiousness, and openness) tended to decline in importance as the vaccination rate and COVID-19 cases grew. Two facets (extraversion and negative emotionality) maintained or increased in their importance as pandemic circumstances changed. This study highlights the influence of personal characteristics on vaccine hesitancy and refusal and the need for additional study on foundational explanations of these behaviors. It calls for additional research on the dynamics of personal characteristics in explaining vaccine hesitancy and refusal. The influence of personality may not be immutable.

Pandemic fatigue or enduring precautionary behaviours? Canadians' long-term response to COVID-19 public health measures.

The long-term dynamics of COVID-19 disease incidence and public health measures may impact individuals' precautionary behaviours as well as support for measures. The objectives of this study were to assess longitudinal changes in precautionary behaviours and support for public health measures. Survey data were collected online from 1030 Canadians in each of 5 cycles in 2020: June 15-July 13; July 22-Aug 8; Sept 7-15; Oct 14-21; and Nov 12-17. Precautionary behaviour increased over the study period in the context of increasing disease incidence. When controlling for the stringency of public health measures and disease incidence, mixed effects logistic regression models showed these behaviours did not significantly change over time. Odds ratios for avoiding contact with family and friends ranged from 0.84 (95% CI 0.59-1.20) in September to 1.25 (95% CI 0.66-2.37) in November compared with July 2020. Odds ratios for attending an indoor gathering ranged from 0.86 (95% CI 0.62-1.20) in August to 1.71 (95% CI 0.95-3.09) in October compared with July 2020. Support for non-essential business closures increased over time with 2.33 (95% CI 1.14-4.75) times higher odds of support in November compared to July 2020. Support for school closures declined over time with lower odds of support in September (OR 0.66 [95% CI 0.45-0.96]), October (OR 0.48 [95% CI 0.26-0.87]), and November (OR 0.39 [95% CI 0.19-0.81]) compared with July 2020. In summary, respondents' behaviour mirrored government guidance between July and November 2020 and supported individual precautionary behaviour and limitations on non-essential businesses over school closures.

Uncovering Hidden Members and Functions of the Soil Microbiome Using De Novo Metaproteomics.

Metaproteomics has been increasingly utilized for high-throughput characterization of proteins in complex environments and has been demonstrated to provide insights into microbial composition and functional roles. However, significant challenges remain in metaproteomic data analysis, including creation of a sample-specific protein sequence database. A well-matched database is a requirement for successful metaproteomics analysis, and the accuracy and sensitivity of PSM identification algorithms suffer when the database is incomplete or contains extraneous sequences. When matched DNA sequencing data of the sample is unavailable or incomplete, creating the proteome database that accurately represents the organisms in the sample is a challenge. Here, we leverage a de novo peptide sequencing approach to identify the sample composition directly from metaproteomic data. First, we created a deep learning model, Kaiko, to predict the peptide sequences from mass spectrometry data and trained it on 5 million peptide-spectrum matches from 55 phylogenetically diverse bacteria. After training, Kaiko successfully identified organisms from soil isolates and synthetic communities directly from proteomics data. Finally, we created a pipeline for metaproteome database generation using Kaiko. We tested the pipeline on native soils collected in Kansas, showing that the de novo sequencing model can be employed as an alternative and complementary method to construct the sample-specific protein database instead of relying on (un)matched metagenomes. Our pipeline identified all highly abundant taxa from 16S rRNA sequencing of the soil samples and uncovered several additional species which were strongly represented only in proteomic data.

Communicating safety precautions can help maintain in-person voter turnout during a pandemic.

Scholars have linked cost and life stress to lower voter turnout with clear implications for voting during the COVID-19 pandemic. We ask whether COVID-19 reduces turnout intention and how election agencies can mitigate this effect. We use a series of six survey and conjoint experiments implemented in samples totalling over 28,000 Canadian respondents collected between July and November of 2020 to show that: 1) priming people to think about COVID-19 reduces turnout intention, especially among those who feel most threatened by the disease; 2) safety measures for in-person voting, such as mandatory masks and physical distancing, can improve safety perceptions and willingness to vote in-person, and 3) providing people information about safety precautions for in-person voting mitigates the negative effect of priming COVID-19. These studies illustrate the importance of both the implementation and communication of measures by election agencies designed to make people safe - and feel safe - while voting in-person.

The ephemeral effects of fact-checks on COVID-19 misperceptions in the United States, Great Britain and Canada.

Widespread misperceptions about COVID-19 and the novel coronavirus threaten to exacerbate the severity of the pandemic. We conducted preregistered survey experiments in the United States, Great Britain and Canada examining the effectiveness of fact-checks that seek to correct these false or unsupported beliefs. Across three countries with differing levels of political conflict over the pandemic response, we demonstrate that fact-checks reduce targeted misperceptions, especially among the groups who are most vulnerable to these claims, and have minimal spillover effects on the accuracy of related beliefs. However, these reductions in COVID-19 misperception beliefs do not persist over time in panel data even after repeated exposure. These results suggest that fact-checks can successfully change the COVID-19 beliefs of the people who would benefit from them most but that their effects are ephemeral.

The correlates and dynamics of COVID-19 vaccine-specific hesitancy.

Most work on COVID-19 vaccine hesitancy has focused on its attitudinal and demographic correlates among individuals, but the characteristics of vaccines themselves also appear to be important. People are more willing to take vaccines with higher reported levels of efficacy and safety. Has this dynamic sparked comparative hesitancy towards specific COVID-19 vaccines? We conduct a series of cross-sectional survey experiments to test for brand-based differences in perceived effectiveness, perceived safety, and vaccination intention. Examining more than 6,200 individuals in a series of cross-sectional surveys, we find considerably more reluctance to take the AstraZeneca and Johnson & Johnson vaccines compared to those from Pfizer and Moderna if offered, despite all vaccines being approved and deemed safe and effective by a federal regulator. Comparative hesitancy towards these vaccines grew over the course of fielding as controversy arose over their link to extremely rare, but serious side effects. Comparative vaccine-specific hesitancy is strongest among people who are usually most open to mass vaccination efforts. Its effects are substantial: most respondents reported a willingness to wait months for their preferred vaccine rather than receive either the AstraZeneca or Johnson & Johnson vaccine immediately. Our findings call for additional research on the determinants and consequences of COVID-19 vaccine-specific hesitancy and communication strategies to minimize this challenge.

Minimal effects from injunctive norm and contentiousness treatments on COVID-19 vaccine intentions: evidence from 3 countries.

Does information about how other people feel about COVID-19 vaccination affect immunization intentions? We conducted preregistered survey experiments in Great Britain (5,456 respondents across 3 survey waves from September 2020 to February 2021), Canada (1,315 respondents in February 2021), and the state of New Hampshire in the United States (1,315 respondents in January 2021). The experiments examine the effects of providing accurate public opinion information to people about either public support for COVID-19 vaccination (an injunctive norm) or public beliefs that the issue is contentious. Across all 3 countries, exposure to this information had minimal effects on vaccination intentions even among people who previously held inaccurate beliefs about support for COVID-19 vaccination or its perceived contentiousness. These results suggest that providing information on public opinion about COVID vaccination has limited additional effect on people's behavioral intentions when public discussion of vaccine uptake and intentions is highly salient.

De novo sequencing and native mass spectrometry revealed hetero-association of dirigent protein homologs and potential interacting proteins in Forsythia × intermedia.

The discovery of dirigent proteins (DPs) and their functions in plant phenol biochemistry was made over two decades ago with Forsythia × intermedia. Stereo-selective, DP-guided, monolignol-derived radical coupling in vitro was then reported to afford the optically active lignan, (+)-pinoresinol from coniferyl alcohol, provided one-electron oxidase/oxidant capacity was present. It later became evident that DPs have several distinct sub-families, presumably with different functions. Some known DPs require other essential enzymes/proteins (e.g. oxidases) for their functions. However, the lack of a fully sequenced genome for Forsythia × intermedia made it difficult to profile other components co-purified with the (+)-pinoresinol forming DP. Herein, we used an integrated bottom-up, top-down, and native mass spectrometry (MS) approach to de novo sequence the extracted proteins via adaptation of our initial report of DP solubilization and purification. Using publicly available transcriptome and genomic data from closely related species, we identified 14 proteins that were putatively associated with either DP function or the cell wall. Although their co-occurrence after extraction and chromatographic separation is suggestive for potential protein-protein interactions, none were found to form stable protein complexes with DPs in native MS under the specific experimental conditions we have explored. Interestingly, two new DP homologs were found and they formed hetero-trimers. Molecular dynamics simulations suggested that similar hetero-trimers were possible between Arabidopsis DP homologs with comparable sequence similarities. Nevertheless, our integrated mass spectrometry method development helped prepare for future investigations directed to the discovery of novel proteins and protein-protein interactions. These advantages can be highly beneficial for plant and microbial research where fully sequenced genomes may not be readily available.

Quantifying contact patterns in response to COVID-19 public health measures in Canada.

BACKGROUND: A variety of public health measures have been implemented during the COVID-19 pandemic in Canada to reduce contact between individuals. The objective of this study was to provide empirical contact pattern data to evaluate the impact of public health measures, the degree to which social contacts rebounded to normal levels, as well as direct public health efforts toward age- and location-specific settings. METHODS: Four population-based cross-sectional surveys were administered to members of a paid panel representative of Canadian adults by age, gender, official language, and region of residence during May (Survey 1), July (Survey 2), September (Survey 3), and December (Survey 4) 2020. A total of 4981 (Survey 1), 2493 (Survey 2), 2495 (Survey 3), and 2491 (Survey 4) respondents provided information about the age and setting for each direct contact made in a 24-h period. Contact matrices were constructed and contacts for those under the age of 18 years imputed. The next generation matrix approach was used to estimate the reproduction number (Rt) for each survey. Respondents with children under 18 years estimated the number of contacts their children made in school and extracurricular settings. RESULTS: Estimated Rt values were 0.49 (95% CI: 0.29-0.69) for May, 0.48 (95% CI: 0.29-0.68) for July, 1.06 (95% CI: 0.63-1.52) for September, and 0.81 (0.47-1.17) for December. The highest proportion of reported contacts occurred within the home (51.3% in May), in 'other' locations (49.2% in July) and at work (66.3 and 65.4% in September and December). Respondents with children reported an average of 22.7 (95% CI: 21.1-24.3) (September) and 19.0 (95% CI 17.7-20.4) (December) contacts at school per day per child in attendance. CONCLUSION: The skewed distribution of reported contacts toward workplace settings in September and December combined with the number of reported school-related contacts suggest that these settings represent important opportunities for transmission emphasizing the need to support and ensure infection control procedures in both workplaces and schools.

Bayesian Inference for Integrating Yarrowia lipolytica Multiomics Datasets with Metabolic Modeling.

Optimizing the metabolism of microbial cell factories for yields and titers is a critical step for economically viable production of bioproducts and biofuels. In this process, tuning the expression of individual enzymes to obtain the desired pathway flux is a challenging step, in which data from separate multiomics techniques must be integrated with existing biological knowledge to determine where changes should be made. Following a design-build-test-learn strategy, building on recent advances in Bayesian metabolic control analysis, we identify key enzymes in the oleaginous yeast Yarrowia lipolytica that correlate with the production of itaconate by integrating a metabolic model with multiomics measurements. To this extent, we quantify the uncertainty for a variety of key parameters, known as flux control coefficients (FCCs), needed to improve the bioproduction of target metabolites and statistically obtain key correlations between the measured enzymes and boundary flux. Based on the top five significant FCCs and five correlated enzymes, our results show phosphoglycerate mutase, acetyl-CoA synthetase (ACSm), carbonic anhydrase (HCO3E), pyrophosphatase (PPAm), and homoserine dehydrogenase (HSDxi) enzymes in rate-limiting reactions that can lead to increased itaconic acid production.

Assessment of Communication Strategies for Mitigating COVID-19 Vaccine-Specific Hesitancy in Canada.

Importance: Ensuring widespread uptake of available COVID-19 vaccinations, each with different safety and efficacy profiles, is essential to combating the unfolding pandemic. Objective: To test communication interventions that may encourage the uptake of less-preferred vaccines. Design, Setting, and Participants: This online survey was conducted from March 24 to 30, 2021, using a nonprobability convenience sample of Canadian citizens aged 18 years or older, with quota sampling to match 2016 Canadian Census benchmarks on age, gender, region, and language. Respondents completed a 2-by-2-by-2 factorial experiment with random assignment of brand (AstraZeneca or Johnson & Johnson), information about the vaccine's effectiveness against symptomatic infection (yes or no), and information about the vaccine's effectiveness at preventing death from COVID-19 (yes or no) before being asked about their willingness to receive their assigned vaccine and their beliefs about its effectiveness. Exposures: Respondents were randomly assigned a vaccine brand (AstraZeneca or Johnson & Johnson) and information about the vaccine's effectiveness against symptomatic COVID-19 infection (yes or no) and at preventing death from COVID-19 (yes or no). Main Outcomes and Measures: Respondents' self-reported likelihood of taking their assigned vaccine if offered (response categories: very likely, somewhat likely, not very likely, or not at all likely, scaled 0-1) and their beliefs about their assigned vaccine's effectiveness (response categories: very effective, somewhat effective, not very effective, or not at all effective, scaled 0-1) were measured. Results: A total of 2556 Canadian adults responded to the survey (median [IQR] age, 50 [34-63] years; 1339 women [52%]). The self-reported likelihood of taking an assigned AstraZeneca or Johnson & Johnson vaccine was higher for respondents given information about their assigned vaccine's effectiveness at preventing death from COVID-19 (b, 0.04; 95% CI, 0.01 to 0.06) and lower among those given information about its overall effectiveness at preventing symptomatic transmission (b, -0.03; 95% CI, -0.05 to 0.00), compared with those who were not given the information. Perceived effectiveness was also higher among those given information about their assigned vaccine's effectiveness at preventing death from COVID-19 (b, 0.03; 95% CI, 0.01 to 0.05) and lower among those given information about their assigned vaccine's overall efficacy at preventing symptomatic infection (b, -0.05; 95% CI, -0.08 to -0.03), compared with those who were not given this information. The interaction between these treatments was neither substantively nor statistically significant. Conclusions and Relevance: These findings suggest that providing information on the effectiveness of less-preferred vaccines at preventing death from COVID-19 is associated with more confidence in their effectiveness and less vaccine-specific hesitancy. These results can inform public health communication strategies to reduce hesitancy toward specific COVID-19 vaccines.

Anti-intellectualism and the mass public's response to the COVID-19 pandemic.

Anti-intellectualism (the generalized distrust of experts and intellectuals) is an important concept in explaining the public's engagement with advice from scientists and experts. We ask whether it has shaped the mass public's response to coronavirus disease 2019 (COVID-19). We provide evidence of a consistent connection between anti-intellectualism and COVID-19 risk perceptions, social distancing, mask usage, misperceptions and information acquisition using a representative survey of 27,615 Canadians conducted from March to July 2020. We exploit a panel component of our design (N = 4,910) to strongly link anti-intellectualism and within-respondent change in mask usage. Finally, we provide experimental evidence of anti-intellectualism's importance in information search behaviour with two conjoint studies (N ~ 2,500) that show that preferences for COVID-19 news and COVID-19 information from experts dissipate among respondents with higher levels of anti-intellectual sentiment. Anti-intellectualism poses a fundamental challenge in maintaining and increasing public compliance with expert-guided COVID-19 health directives.

Socio-demographic disparities in knowledge, practices, and ability to comply with COVID-19 public health measures in Canada.

OBJECTIVES: The effectiveness of public health interventions for mitigation of the COVID-19 pandemic depends on individual attitudes, compliance, and the level of support available to allow for compliance with these measures. The aim of this study was to describe attitudes and behaviours towards the Canadian COVID-19 public health response, and identify risk-modifying behaviours based on socio-demographic characteristics. METHODS: A cross-sectional online survey was administered in May 2020 to members of a paid panel representative of the Canadian population by age, gender, official language, and region of residence. A total of 4981 respondents provided responses for indicators of self-reported risk perceptions, attitudes, and behaviours towards COVID-19 public health measures. RESULTS: More than 90% of respondents reported confidence in the ability to comply with a variety of public health measures. However, only 51% reported preparedness for illness in terms of expectation to work if sick or access to paid sick days. Risk perceptions, attitudes, and behaviours varied by demographic variables. Men, younger age groups, and those in the paid workforce were less likely to consider public health measures to be effective, and had less confidence in their ability to comply. Approximately 80% of respondents reported that parents provided childcare and 52% reported that parents in the workforce provided childcare while schools were closed. CONCLUSION: Policies to help address issues of public adherence include targeted messaging for men and younger age groups, social supports for those who need to self-isolate, changes in workplace policies to discourage presenteeism, and provincially co-ordinated masking and safe school policies.

RéSUMé: OBJECTIFS: L'efficacité des mesures d'intervention en santé publique pour atténuer la pandémie de COVID-19 dépend des attitudes individuelles, de la conformité, ainsi que du niveau d'aide disponible pour que les mesures soient respectées. Notre étude visait à décrire les attitudes et les comportements à l'égard de la riposte de la santé publique canadienne à la COVID-19 et à cerner les comportements modificateurs du risque d'après les caractéristiques sociodémographiques. MéTHODE: Un sondage en ligne transversal a été administré en mai 2020 aux membres d'un comité rémunéré représentatif de l'âge, du sexe, des langues officielles et des régions de résidence de la population canadienne. En tout, 4 981 personnes ont fourni des réponses à des questions indicatrices de leurs perceptions du risque, de leurs attitudes et de leurs comportements autodéclarés à l'égard des mesures de santé publique liées à la COVID-19. RéSULTATS: Plus de 90 % des répondants se sont dits certains de leur capacité de respecter de nombreuses mesures de santé publique. Par contre, 51 % seulement ont dit être préparés à respecter ces mesures s'ils attrapaient la maladie, c'est-à-dire pouvoir s'absenter du travail ou avoir droit à des congés de maladie payés. Les perceptions du risque, les attitudes et les comportements variaient selon les caractéristiques démographiques. Les hommes, les jeunes et les personnes ayant un emploi rémunéré étaient moins susceptibles de trouver les mesures de santé publique efficaces et moins sûrs de leur capacité de les respecter. Environ 80 % des répondants ont indiqué que la garde des enfants était assurée par les parents, et 52 % ont indiqué que la garde des enfants quand les écoles étaient fermées était assurée par des parents ayant un emploi. CONCLUSION: Des messages ciblant les hommes et les jeunes, des soutiens sociaux aux personnes ayant besoin de s'isoler, des changements dans les politiques en milieu de travail pour dissuader le présentéisme, ainsi que des politiques de port du masque et de sécurité à l'école coordonnées à l'échelle provinciale sont des mesures susceptibles d'atténuer les problèmes d'adhésion du public.

Flying blind, or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification.

Mass spectrometry-based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics, and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo methods infer peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph-based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.

Constructing a Tandem Mass Spectral Library for Forensic Ricin Identification.

Ricin, a protein found in castor seeds, is a lethal toxin that is designated as a category 2 select agent, and cases of attempted ricin poisoning are relatively common. Many methods to detect protein toxins such as ricin use targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify toxin peptides, usually tryptic peptides. The successful use of untargeted methods has also been reported. However, the use of untargeted proteomics methods, including database search, for peptide and protein identification is less common in forensic practice and may be unfamiliar to forensic science practitioners. Here, we propose a method to create spectral libraries of tryptic ricin peptides and use these libraries for ricin identification by spectral library search, which may be more familiar to forensic scientists because of the use of spectral libraries in small molecule identification. Peptide spectral libraries offer a direct comparison to an authentic standard, a key element of forensic analysis, but have not previously been used in a forensic context. To construct these spectral libraries, two pure ricin samples (one from a proposed standard reference material) were digested with trypsin and analyzed using a standard shotgun LC-MS/MS protocol. Spectral libraries were created from resulting tryptic peptides identified from filtered search results from four database search tools. The library was then used in a search using SpectraST on forensically realistic castor seed extracts. These castor seed samples were made using the crude methods commonly encountered in real-world ricin cases. Analysis showed that the spectral library search resulted in more peptides identified from crude castor seed samples compared to MS-GF+ and Sequest plus Percolator database searches. These results, the first published use of spectral library search to detect protein toxins in forensically relevant samples, suggest that computational comparison of putative ricin peptide spectra to library spectra can be an effective method to detect ricin in an unknown sample. Data are available via ProteomeXchange with identifier PXD013711.

Uniformly 15N-Labeled Recombinant Ricin A-Chain as an Internal Retention Time Standard for Increased Confidence in Forensic Identification of Ricin by Untargeted Nanoflow Liquid Chromatography-Tandem Mass Spectrometry.

Ricin, a toxic protein from the castor plant, is of forensic and biosecurity interest because of its high toxicity and common occurrence in crimes and attempted crimes. Qualitative methods to detect ricin are therefore needed. Untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics methods are well suited because of their high specificity. Specificity in LC-MS/MS comes from both the LC and MS components. However, modern untargeted proteomics methods often use nanoflow LC, which has less reproducible retention times than standard-flow LC, making it challenging to use retention time as a point of identification in a forensic assay. We address this challenge by using retention times relative to a standard, namely, the uniformly 15N-labeled ricin A-chain produced recombinantly in a bacterial expression system. This material, added as an internal standard prior to trypsin digestion, produces a stable-isotope-labeled standard for every ricin tryptic peptide in the sample. We show that the MS signals for 15N and natural isotopic abundance ricin peptides are distinct, with mass shifts that correspond to the numbers of nitrogen atoms in each peptide or fragment. We also show that, as expected, labeled and unlabeled peptides coelute, with relative retention time differences of less than 0.2%.

Probabilistic Limit of Detection for Ricin Identification Using a Shotgun Proteomics Assay.

Robust and highly specific methods for the detection of the protein toxin ricin are of interest to the law enforcement community. In previous studies, methods based on liquid chromatography-tandem mass spectrometry shotgun proteomics have been proposed. The successful implementation of this approach relies on specific data evaluation criteria addressing (1) the quality of the mass spectrometric data, (2) the confidence of peptide identifications (peptide-spectrum matches), and (3) the number and sequence specificity of peptides detected. We present such data evaluation criteria and use a novel approach to establish the limit of detection for this ricin assay. Specifically, we use logistic regression to determine the probability of detection for individual ricin peptides at different concentrations. We then apply basic rules from probability theory, combining these individual peptide probabilities into an overall assay limit of detection. This procedure yields an assay limit of detection for ricin at 42.5 ng on column or 21.25 ng/µL for a 2-µL injection. We also show that, despite the conventional wisdom that detergents are deleterious to mass spectrometric analyses, the presence of Tween-20 did not prevent detection of ricin peptides, and indeed assays performed in buffers that included Tween-20 gave better results than assays performed using other buffer formulations with or without detergent removal.

Defending Our Public Biological Databases as a Global Critical Infrastructure.

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world's primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly "retrofitted" mitigations. This Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

Applications and challenges of forensic proteomics.

Mass spectrometry-based proteomics has been a useful tool for addressing numerous questions in basic biology research for many years. This success, combined with the maturity of mass spectrometric instrumentation, the ever-increasing availability of protein sequence databases derived from genome sequencing, and the growing sophistication of data analysis methods, places proteomics in a position to have an important role in biological forensics. Because proteins contain information about genotype (sequence) and phenotype (expression levels), proteomics methods can both identify biological samples and characterize the conditions that produced them. In addition to serving as a valuable orthogonal method to genomic analyses, proteomics can be used in cases where nucleic acids are absent, degraded, or uninformative. Mass spectrometry provides both broad applicability and exquisite specificity, often without customized detection reagents like primers or antibodies. This review briefly introduces proteomics methods, and surveys a variety of forensic applications (including criminal justice, historical, archaeological, and national security areas). Finally, challenges and crucial areas for further research are addressed.

Perspective on Improving Environmental Monitoring of Biothreats.

For more than a decade, the United States has performed environmental monitoring by collecting and analyzing air samples for a handful of biological threat agents (BTAs) in order to detect a possible biological attack. This effort has faced numerous technical challenges including timeliness, sampling efficiency, sensitivity, specificity, and robustness. The cost of city-wide environmental monitoring using conventional technology has also been a challenge. A large group of scientists with expertise in bioterrorism defense met to assess the objectives and current efficacy of environmental monitoring and to identify operational and technological changes that could enhance its efficacy and cost-effectiveness, thus enhancing its value. The highest priority operational change that was identified was to abandon the current concept of city-wide environmental monitoring because the operational costs were too high and its value was compromised by low detection sensitivity and other environmental factors. Instead, it was suggested that the focus should primarily be on indoor monitoring and secondarily on special-event monitoring because objectives are tractable and these operational settings are aligned with likelihood and risk assessments. The highest priority technological change identified was the development of a reagent-less, real-time sensor that can identify a potential airborne release and trigger secondary tests of greater sensitivity and specificity for occasional samples of interest. This technological change could be transformative with the potential to greatly reduce operational costs and thereby create the opportunity to expand the scope and effectiveness of environmental monitoring.