Clinical Utility of Insulin-Like Growth Factor 1 and 2; Determination by High Resolution Mass Spectrometry

Measurement of insulin-like growth factor-1 (IGF-I) has utility for the diagnosis and management of growth disorders, but inter-assay comparison of results has been complicated by a multitude of reference standards, antibodies, detection methods, and pre-analytical preparation strategies. We developed a quantitative LC-MS method for intact IGF-I, which has advantages in throughput and complexity when compared to mass spectrometric approaches that rely on stable isotope dilution analysis of tryptic peptides. Since the method makes use of full-scan data, the assay was easily extended to provide quantitative measurement of IGF-II using the same assay protocol. The validated LC-MS assay for IGF-I and IGF-II provides accurate results across the pediatric and adult reference range and is suitable for clinical use.     

A very large repeating unit of mouse DNA containing the 18S, 28S and 5.8S rRNA genes

The organization of the 18S, 28S and 5.8S rRNA genes in the mouse has been elucidated by mapping with restriction endonucleases Eco RI, Hind III and Bam HI. Ribosomal DNA fragments were detected in electrophoretically fractionated digests of total nuclear DNA by in situ hybridization with radioiodinated rRNAs or with complementary RNA synthesized directly on rRNA templates. A map of the rDNA which includes 13 restriction sites was constructed from the sizes of rDNA fragments and their labeling by different probes The map indicates that the rRNA genes lie within remarkably large units of reiterated DNA, at least 44,000 base pairs long. At least two, and possibly four, classes of repeating unit can be distinguished, the heterogeneity probably residing in the very large nontranscribed spacer region. The 5.8S rRNA gene lies in the transcribed region between the 18S and 28S genes.     

The impact of ADHD on morality development

Attention deficit hyperactive disorder (ADHD) is one of the most commonly diagnosed childhood mental disorders. This pervasive disorder can affect all aspects of the child’s life, including, but not limited to: peer relations, adult relations and intellectual development. As a direct result of ADHD, many of these deficiencies pervade through the child’s life into adulthood. Although there is a growing number of literature focusing on the sequela of ADHD, especially social deviance, most of the literature’s scope is limited to the connection between ADHD and criminality. This finite perspective provides little insight into the developmental characteristics which actually link ADHD to criminality. The most glaring example of an obscured developmental link is that of moral judgment. The following is an attempt to draw a meaningful connection between deficient moral development and ADHD, especially as it relates to attachment theory. Connecting previous research relevant to the topic as well as time-tested psychological theories on morality and attachment will serve to validate this claim.     

Genetic Similarity of Island Populations of Tent Caterpillars during Successive Outbreaks

Cyclic or fluctuating populations experience regular periods of low population density. Genetic bottlenecks during these periods could give rise to temporal or spatial genetic differentiation of populations. High levels of movement among increasing populations, however, could ameliorate any differences and could also synchronize the dynamics of geographically separated populations. We use microsatellite markers to investigate the genetic differentiation of four island and one mainland population of western tent caterpillars, Malacosoma californicum pluviale, in two periods of peak or pre-peak density separated by 8 years. Populations showed high levels of genetic variation and little genetic differentiation either temporally between peaks or spatially among sites. Mitochondrial haplotypes were also shared between one island population and one mainland population in the two years studied. An isolation-by-distance analysis showed the F_ST values of the two geographically closest populations to have the highest level of differentiation in both years. We conclude that high levels of dispersal among populations maintain both synchrony of population dynamics and override potential genetic differentiation that might occur during population troughs. As far we are aware, this is the first time that genetic similarity between temporally separated population outbreaks in insects has been investigated. A review of genetic data for both vertebrate and invertebrate species of cyclic animals shows that a lack of spatial genetic differentiation is typical, and may result from high levels of dispersal associated with fluctuating dynamics.     

The 2012/2013 ABRF Proteomic Research Group Study: Assessing Longitudinal Intralaboratory Variability in Routine Peptide Liquid Chromatography Tandem Mass Spectrometry Analyses*

Questions concerning longitudinal data quality and reproducibility of proteomic laboratories spurred the Protein Research Group of the Association of Biomolecular Resource Facilities (ABRF-PRG) to design a study to systematically assess the reproducibility of proteomic laboratories over an extended period of time. Developed as an open study, initially 64 participants were recruited from the broader mass spectrometry community to analyze provided aliquots of a six bovine protein tryptic digest mixture every month for a period of nine months. Data were uploaded to a central repository, and the operators answered an accompanying survey. Ultimately, 45 laboratories submitted a minimum of eight LC-MSMS raw data files collected in data-dependent acquisition (DDA) mode. No standard operating procedures were enforced; rather the participants were encouraged to analyze the samples according to usual practices in the laboratory. Unlike previous studies, this investigation was not designed to compare laboratories or instrument configuration, but rather to assess the temporal intralaboratory reproducibility. The outcome of the study was reassuring with 80% of the participating laboratories performing analyses at a medium to high level of reproducibility and quality over the 9-month period. For the groups that had one or more outlying experiments, the major contributing factor that correlated to the survey data was the performance of preventative maintenance prior to the LC-MSMS analyses. Thus, the Protein Research Group of the Association of Biomolecular Resource Facilities recommends that laboratories closely scrutinize the quality control data following such events. Additionally, improved quality control recording is imperative. This longitudinal study provides evidence that mass spectrometry-based proteomics is reproducible. When quality control measures are strictly adhered to, such reproducibility is comparable among many disparate groups. Data from the study are available via ProteomeXchange under the accession code PXD002114.The broad-reaching use and application of mass spectrometry-based proteomics in the international research community continues to exponentially grow and expand. As the technology has developed and practitioners have become skilled in performing complex workflows, the community has not only gained interest in assessing data across laboratories but also in maintaining consistent quality control within a laboratory. Koecher et al. raised the issue of quality control measures and how this aspect of mass spectrometry-based proteomics is generally neglected in scientific publications (1). Fortunately, studies characterizing the stability of liquid chromatography-tandem MS (LC-MSMS)¹ quality control performance among numerous laboratories are emerging. The relationship between sample preparation schemes, data acquisition and reduction strategies, and bioinformatic analyses have been comprehensively reviewed by Tabb (2).Several studies exist where intra- and interlaboratory reproducibility between multiple sites has been assessed under different settings. Perhaps the most systematic and detailed of these investigations are from the Human Proteome Organization (HuPO) test sample working group (3); the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (NCI CPTAC) (4); and the ProteoRed Consortium (5, 6). The HuPO group utilized an equimolar mixture of 20 highly purified recombinant human proteins (5 pmol per protein) distributed to 27 different laboratories and analyzed without constraint according to optimized LCMS and database search protocols from each of the laboratories (3). The study was not an assessment of instrument performance for highly sensitive detection of proteins, as all participating laboratories had acquired raw data of sufficient quality to identify all 20 proteins (and a specific subset of tryptic peptides). The study revealed, however, that discrepancies in peptide identification and protein assignment were the result of differences in data analysis strategies rather than data collection.The NCI CPTAC group used a standardized Saccharomyces cerevisiae proteome digest that was analyzed on ion-trap-based LCMS platforms in five independent laboratories according to both an established standard operating procedure (SOP) and with no SOP constraint (4). All data analysis was centralized, and thus, any observed variations were entirely because of the LCMS platform. By applying the performance metrics developed by Rudnick et al. (7), several key points emerged: (1) as expected, intralaboratory variation was less than interlaboratory variation; and (2) overall, the interlaboratory variation in peptide identifications and some of the other performance metrics were comparable between instruments, although there were large differences in the average values for some metrics (e.g. MS1 signal intensity, dynamic sampling).The ProteoRed Consortium initiated the ProteoRed Multicenter Experiment for Quality Control (PMEQC) (5, 6). This longitudinal QC multicenter study involved 12 institutes, and was designed to assess: (1) intralaboratory repeatability of LC-MSMS proteomic data; (2) interlaboratory reproducibility; and (3) reproducibility across multiple instrument platforms. Participants received samples of undigested or tryptically digested yeast proteins and were requested to follow strict analytical guidelines. Data analysis was centralized and performed under standard procedures using a common workflow. The study revealed that the overall performance with respect to metrics such as reproducibility, sensitivity, dynamic range etc. was directly related to the degree of operator expertise, and less dependent on instrumentation.Several studies not specifically focused on quality control have also yielded insight into proteomic reproducibility. The HuPO plasma proteome project (HuPO PPP) distributed 20 human samples (five serum plus 3 × 5 plasma samples treated with three different anticoagulants) to 35 laboratories spanning 13 countries (8). The purpose of this large-scale study was not to assess reproducibility per se, but rather to generate the largest and most comprehensive data set on the protein composition of human plasma/serum. On a smaller scale, the ISB standard 18 protein mixture (purified proteins from cow, horse, rabbit, chicken, E. coli, and B. licheniformus) was also assessed between laboratories on eight different LCMS platforms (9). These data reside in a comprehensive, multiplatform database as a resource for the proteomic community. Additional interlaboratory assessments have consisted of multiple reaction monitoring-based measurements of peptides/proteins in plasma (10, 11) and protein–protein interactions at both the biochemical and proteomic level (12).For team leaders/directors of proteomic laboratories and any researcher collaborating with such groups, major questions that may arise concerning data consistency are: how well are quality controls being implemented in the daily operations? Do the quality control measures effectively support data reproducibility? To address this, the Protein Research Group of the Association of Biomolecular Resource Facilities (ABRF-PRG) designed a study whereby LC-MSMS data obtained from the analysis of a commercially available bovine protein mixture predigested with trypsin were collected at routine intervals over a period of 9 months. Raw MS data files from a total of 64 participating laboratories were accumulated, and HPLC and MS performance were evaluated through QC metrics (13). The main impetus of the study was to recognize key sources of variability in HPLC and MS analyses under extended and routine operating conditions for each laboratory and to catalog the state of quality control in a diverse set of proteomic laboratories.No standard operating protocol was imposed on the participants; instead, contributors were encouraged to employ the methods that were typically applied in individual laboratories. Optimization of instrument methods on the provided sample was discouraged. A survey was conducted with each sample submission to catalog individual laboratory practices, instrument configurations, acquisition settings, including routine and nonroutine maintenance procedures. Unlike previous investigations where emphasis was placed on the preparation, distribution, and evaluation of protein standards to appraise and/or standardize LCMS platforms between laboratories, the key interest in this study was purely to determine the intralaboratory performance, reproducibility, and consistency of participating laboratories over an extended period of time.The rapidly expanding number of proteomic laboratories have incorporated divergent HPLC systems, mass spectrometers, solvent systems, columns etc. As a result, analyzing data from a large number of laboratories necessitates tools that can accommodate data from a broad range of platforms. For example, to expect a small laboratory with a decade-old three-dimensional ion trap mass spectrometer to achieve the same sensitivity as a laboratory with a high-resolution hybrid instrument would be unfair. Correspondingly, the data analysis needs to include axes beyond simple peptide-level sensitivity. Nevertheless, the laboratory with the older instrumentation may be consistently better at maximizing performance from the chosen instrument platform compared with a laboratory with the latest high-end equipment.The focus of this study was to estimate the degree of variability in intralaboratory performance over a 9-month period. This goal was achieved using quality metrics that are applicable to most LC-MSMS workflows. The inclusion of data from many laboratories will enable the proteomic community to determine the current state of quality control within a typical laboratory. The survey data enabled the mapping of some alterations in instrument performance to documented laboratory events, e.g. mass spectrometer calibration. The study was designed neither to compare one laboratory with another, nor to discriminate between classes of instrumentation.Questions of data quality and performance in the proteomic community are appropriately aligned with the heightened awareness of a perceived lack of reproducibility of scientific findings in general (1). This community has endeavored to provide tools to assess proteomic data quality, and this study provides additional insight into the application of such tools and the quality of data within respective laboratories.     

Speeding Up Ecological and Evolutionary Computations in R; Essentials of High Performance Computing for Biologists

Computation has become a critical component of research in biology. A risk has emerged that computational and programming challenges may limit research scope, depth, and quality. We review various solutions to common computational efficiency problems in ecological and evolutionary research. Our review pulls together material that is currently scattered across many sources and emphasizes those techniques that are especially effective for typical ecological and environmental problems. We demonstrate how straightforward it can be to write efficient code and implement techniques such as profiling or parallel computing. We supply a newly developed R package (aprof) that helps to identify computational bottlenecks in R code and determine whether optimization can be effective. Our review is complemented by a practical set of examples and detailed Supporting Information material (S1–S3 Texts) that demonstrate large improvements in computational speed (ranging from 10.5 times to 14,000 times faster). By improving computational efficiency, biologists can feasibly solve more complex tasks, ask more ambitious questions, and include more sophisticated analyses in their research.

This is part of the PLOS Computational Biology Education collection.

     

Differences in the Metabolic Rates of Exploited and Unexploited Fish Populations: A Signature of Recreational Fisheries Induced Evolution?

Non-random mortality associated with commercial and recreational fisheries have the potential to cause evolutionary changes in fish populations. Inland recreational fisheries offer unique opportunities for the study of fisheries induced evolution due to the ability to replicate study systems, limited gene flow among populations, and the existence of unexploited reference populations. Experimental research has demonstrated that angling vulnerability is heritable in Largemouth Bass Micropterus salmoides, and is correlated with elevated resting metabolic rates (RMR) and higher fitness. However, whether such differences are present in wild populations is unclear. This study sought to quantify differences in RMR among replicated exploited and unexploited populations of Largemouth Bass. We collected age-0 Largemouth Bass from two Connecticut drinking water reservoirs unexploited by anglers for almost a century, and two exploited lakes, then transported and reared them in the same pond. Field RMR of individuals from each population was quantified using intermittent-flow respirometry. Individuals from unexploited reservoirs had a significantly higher mean RMR (6%) than individuals from exploited populations. These findings are consistent with expectations derived from artificial selection by angling on Largemouth Bass, suggesting that recreational angling may act as an evolutionary force influencing the metabolic rates of fishes in the wild. Reduced RMR as a result of fisheries induced evolution may have ecosystem level effects on energy demand, and be common in exploited recreational populations globally.