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Protein-lysine methylation is a common posttranslational modification (PTM) throughout the human proteome that plays important roles in diverse biological processes. In humans, there are >100 known and candidate protein lysine methyltransferases (PKMTs), many of which are linked to human diseases. Methyltransferase-like protein 21C (METTL21C) is a PKMT implicated in muscle biology that has been reported to methylate valosin-containing protein/p97 (VCP) and heat shock 70-kDa protein 8 (HSPA8). However, a clear in vitro methyltransferase activity for METTL21C remains yet to be demonstrated, and whether it is an active enzyme that directly methylates substrate(s) in vivo is unclear. Here, we used an unbiased biochemistry-based screening assay coupled to MS, which identified alanine tRNA synthetase 1 (AARS1) as a direct substrate of METTL21C. We found that METTL21C catalyzes methylation of Lys-943 of AARS1 (AARS1-K943me) both in vitro and in vivo. In vitro METTL21C-mediated AARS1 methylation was independent of ATP or tRNA molecules. Unlike for AARS1, and in conflict with previous reports, we did not detect METTL21C methylation of VCP and HSPA8. AARS1-K943 methylation in HEK293T cells depends upon METTL21C levels. Finally, METTL2C was almost exclusively expressed in muscle tissue, and, accordingly, we detected METTL21C-catalyzed methylation of AARS1 in mouse skeletal muscle tissue. These results reveal that AARS1 is a bona fide in vitro substrate of METTL21C and suggest a role for the METTL21C-AARS1 axis in the regulation of protein synthesis in muscle tissue. Moreover, our study describes a straightforward protocol for elucidating the physiological substrates of poorly characterized or uncharacterized PKMTs.

SUMMARY The γ-chain receptor dimerizes with complexes of the cytokines interleukin-2 (IL-2), IL-4, IL-7, IL-9, IL-15, and IL-21 and their corresponding “private” receptors. These cytokines have existing uses and future potential as immune therapies because of their ability to regulate the abundance and function of specific immune cell populations. Here, we build a binding reaction model for the ligand-receptor interactions of common γ-chain cytokines, which includes receptor trafficking dynamics, enabling quantitative predictions of cell-type-specific response to natural and engineered cytokines. We then show that tensor factorization is a powerful tool to visualize changes in the input-output behavior of the family across time, cell types, ligands, and concentrations. These results present a more accurate model of ligand response validated across a panel of immune cell types as well as a general approach for generating interpretable guidelines for manipulation of cell-type-specific targeting of engineered ligands., Graphical Abstract, In brief Farhat et al. develop a mechanistic model of the common γ-chain receptor cytokines incorporating the structure of receptor-ligand interaction and trafficking. This model can predict the response to these cytokines, alone and in combination, and changes in binding affinity, enabling more rational cytokine engineering.

In the yeast Saccharomyces cerevisiae, genomic instability in rDNA repeat sequences is an underlying cause of cell aging and is suppressed by the chromatin-silencing factor Sir2. In humans, rDNA instability is observed in cancers and premature aging syndromes, but its underlying mechanisms and functional consequences remain unclear. Here, we uncovered a pivotal role of sirtuin 7 (SIRT7), a mammalian Sir2 homolog, in guarding against rDNA instability and show that this function of SIRT7 protects against senescence in primary human cells. We found that, mechanistically, SIRT7 is required for association of SNF2H (also called SMARCA5, SWI/SNF-related matrix-associated actin-dependent regulator of chromatin, subfamily A, member 5), a component of the nucleolar heterochromatin-silencing complex NoRC, with rDNA sequences. Defective rDNA–heterochromatin silencing in SIRT7-deficient cells unleashed rDNA instability, with excision and loss of rDNA gene copies, which in turn induced acute senescence. Mounting evidence indicates that accumulation of senescent cells significantly contributes to tissue dysfunction in aging-related pathologies. Our findings identify rDNA instability as a driver of mammalian cellular senescence and implicate SIRT7-dependent heterochromatin silencing in protecting against this process.

We thank Pal Falnes, Jerry Pelletier, and Julien Sage for helpful discussion, Lauren Brown and William Devine for SDS-1-021, and members of the Gozani and Mazur laboratories for critical reading of the manuscript. This work was supported in part by grants from the NIH to S.M.C. (K99CA190803), M.P.K. (5K08CA218690-02), J.A.P. (R35GM118173), M.C.B. (1DP2HD084069-01), J.S. (1R35GM119721), I.T. (R01CA202021), P.K.M. (R00CA197816, P50CA070907, and P30CA016672), and O.G. (R01GM079641). J.E.E. received support from Stanford ChEM-H, and A.M. was supported by the MD Anderson Moonshot Program. I.T. is a Junior 2 Research Scholar of the Fonds de Recherche du Quebec - Sante (FRQ-S). P.K.M. is supported by the Neuroendocrine Tumor Research Foundation and American Association for Cancer Research and is the Andrew Sabin Family Foundation Scientist and CPRIT scholar (RR160078). S.H. is supported by a Deutsche Forschungsgemeinschaft Postdoctoral Fellowship. J.W.F. is supported by 5T32GM007276. (K99CA190803 - NIH; 5K08CA218690-02 - NIH; R35GM118173 - NIH; 1DP2HD084069-01 - NIH; 1R35GM119721 - NIH; R01CA202021 - NIH; R00CA197816 - NIH; P50CA070907 - NIH; P30CA016672 - NIH; R01GM079641 - NIH; Stanford ChEM-H; MD Anderson Moonshot Program; Neuroendocrine Tumor Research Foundation; American Association for Cancer Research; Deutsche Forschungsgemeinschaft Postdoctoral Fellowship; 5T32GM007276)

In eukaryotes, precursor mRNA (pre-mRNA) splicing removes non-coding intron sequences to produce mature mRNA. This removal is controlled in part by RNA-binding proteins that regulate alternative splicing decisions through interactions with the splicing machinery. RNA binding motif protein 25 (RBM25) is a putative splicing factor strongly conserved across eukaryotic lineages. However, the role of RBM25 in global splicing regulation and its cellular functions are unknown. Here we show that RBM25 is required for the viability of multiple human cell lines, suggesting that it could play a key role in pre-mRNA splicing. Indeed, transcriptome-wide analysis of splicing events demonstrated that RBM25 regulates a large fraction of alternatively spliced exons throughout the human genome. Moreover, proteomic analysis indicated that RBM25 interacts with components of the early spliceosome and regulators of alternative splicing. Previously, we identified an RBM25 species that is mono-methylated at lysine 77 (RBM25K77me1), and here we used quantitative mass spectrometry to show that RBM25K77me1 is abundant in multiple human cell lines. We also identified a region of RBM25 spanning Lys-77 that binds with high affinity to serine- and arginine-rich splicing factor 2 (SRSF2), a crucial protein in exon definition, but only when Lys-77 is unmethylated. Together, our findings uncover a pivotal role for RBM25 as an essential regulator of alternative splicing and reveal a new potential mechanism for regulation of pre-mRNA splicing by lysine methylation of a splicing factor.

Protein methylation plays an integral role in cellular signaling, most notably by modulating proteins bound at chromatin, and increasingly through regulation of non-histone proteins. One central challenge in understanding how methylation acts in signaling is identifying and measuring protein methylation. This includes locus-specific modification of histones, on individual non-histone proteins, and globally across the proteome. Protein methylation has traditionally been studied using candidate approaches such as methylation-specific antibodies, mapping of post-translational modifications by mass spectrometry, and radioactive labeling to characterize methylation on target proteins. Recent developments have provided new approaches to identify methylated proteins, measure methylation levels, identify substrates of methyltransferase enzymes, and match methylated proteins to methyl-specific reader domains. Methyl-binding protein domains and improved antibodies with broad specificity for methylated proteins are being used to characterize the “protein methylome”. They also have the potential to be used in high-throughput assays for inhibitor screens and drug development. These tools are often coupled to improvements in mass spectrometry to quickly identify methylated residues, and to protein microarrays, where they can be used to screen for methylated proteins. Finally, new chemical biology strategies are being used to probe the function of methyltransferases, demethylases and methyl-binding “reader” domains. These tools are creating a “system-level” understanding of protein methylation, and integrating protein methylation into broader signaling processes.

Lysine methylation of histone proteins regulates chromatin dynamics and plays important roles in diverse physiological and pathological processes. However, beyond histone proteins, the proteome-wide extent of lysine methylation remains largely unknown. We have engineered the naturally occurring MBT domain repeats of L3MBTL1 to serve as a universal affinity reagent for detecting, enriching, and identifying proteins carrying a mono- or di-methylated lysine. The domain is broadly specific for methylated lysine (“pan-specific”) and can be applied to any biological system. We have used our approach to demonstrate that SIRT1 is a substrate of the methyltransferase G9a both in vitro and in cells, to perform proteome-wide detection and enrichment of novel methylated proteins, and to identify candidate in-cell substrates of G9a and the related methyltransferse GLP. Together, our results demonstrate a powerful new approach for global and quantitative analysis of methylated lysine, and they represent the first systems biology understanding of lysine methylation.

Asthma is associated with an increased risk of mild cognitive impairment and dementia. Depression and oral corticosteroid use are associated with atrophy of the hippocampus and are common in asthma. However, minimal neuroimaging data are available in asthma patients.We conducted a retrospective analysis of 1,287 adult participants from the Dallas Heart Study, an epidemiological sample of Dallas County residents. Study outcome variables were hippocampal volumes measured by FreeSurfer. ANOVA was used to examine a gender difference in hippocampal volumes. General Linear Models (GLM) were conducted to examine asthma diagnosis association with hippocampal volumes.The prevalence rate of asthma among our study sample was 10.8% with 9.6% in males and 11.7% in females. After controlling for demographic characteristics, participants with asthma had significantly smaller total, right, and left hippocampal volumes than those without asthma. The association of asthma with smaller hippocampal volume was significant among males but not among females.Hippocampal volume in a large and diverse sample of adults was significantly smaller in people with asthma as compared to those without asthma. These findings suggest that asthma may be associated with structural brain differences. Thus, medical illnesses without obvious direct neurodegenerative or even vascular involvement can be associated with brain changes. Because the hippocampus is a brain region involved in memory formation, these findings may have implications for treatment adherence that could have important implications for asthma treatment. Study limitations are the reliance on a self-reported asthma diagnosis and lack of additional asthma clinical information.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal form of cancer with few therapeutic options. We found that levels of the lysine methyltransferase SMYD2 (SET and MYND domain 2) are elevated in PDAC and that genetic and pharmacological inhibition of SMYD2 restricts PDAC growth. We further identified the stress response kinase MAPKAPK3 (MK3) as a new physiologic substrate of SMYD2 in PDAC cells. Inhibition of MAPKAPK3 impedes PDAC growth, identifying a potential new kinase target in PDAC. Finally, we show that inhibition of SMYD2 cooperates with standard chemotherapy to treat PDAC cells and tumors. These findings uncover a pivotal role for SMYD2 in promoting pancreatic cancer.

Occurrence of the BCR-ABL(T315I) gatekeeper mutation is among the most pressing challenges in the therapy of chronic myeloid leukemia (CML). Several BCR-ABL inhibitors have multiple targets and pleiotropic effects that could be exploited for their synergistic potential. Testing combinations of such kinase inhibitors identified a strong synergy between danusertib and bosutinib that exclusively affected CML cells harboring BCR-ABL(T315I). To elucidate the underlying mechanisms, we applied a systems-level approach comprising phosphoproteomics, transcriptomics and chemical proteomics. Data integration revealed that both compounds targeted Mapk pathways downstream of BCR-ABL, resulting in impaired activity of c-Myc. Using pharmacological validation, we assessed that the relative contributions of danusertib and bosutinib could be mimicked individually by Mapk inhibitors and collectively by downregulation of c-Myc through Brd4 inhibition. Thus, integration of genome- and proteome-wide technologies enabled the elucidation of the mechanism by which a new drug synergy targets the dependency of BCR-ABL(T315I) CML cells on c-Myc through nonobvious off targets.

The limited clinical success of therapeutics targeting cellular signaling processes is due to multiple factors, including off-target effects and complex feedback regulation encoded within the signaling network. To understand these effects, chemical proteomics and chemical genetics tools have been developed to map the direct targets of kinase inhibitors, determine the network-level response to inhibitor treatment, and to infer network topology. Here we provide an overview of chemical phosphoproteomic and chemical genetic methods, including specific examples where these methods have been applied to yield biological insight regarding network structure and the system-wide effects of targeted therapeutics. The challenges and caveats associated with each method are described, along with approaches being used to resolve some of these issues. With the broad array of available techniques the next decade should see a rapid improvement in our understanding of signaling networks regulation and response to targeted perturbations, leading to more efficacious therapeutic strategies.

MS/MS is a widely used method for proteome-wide analysis of protein expression and PTMs. The thousands of MS/MS spectra produced from a single experiment pose a major challenge for downstream analysis. Standard programs, such as MASCOT, provide peptide assignments for many of the spectra, including identification of PTM sites, but these results are plagued by false-positive identifications. In phosphoproteomic experiments, only a single peptide assignment is typically available to support identification of each phosphorylation site, and hence minimizing false positives is critical. Thus, tedious manual validation is often required to increase confidence in the spectral assignments. We have developed phoMSVal, an open-source platform for managing MS/MS data and automatically validating identified phosphopeptides. We tested five classification algorithms with 17 extracted features to separate correct peptide assignments from incorrect ones using over 2600 manually curated spectra. The naïve Bayes algorithm was among the best classifiers with an AUC value of 97% and PPV of 97% for phosphotyrosine data. This classifier required only three features to achieve a 76% decrease in false positives as compared with MASCOT while retaining 97% of true positives. This algorithm was able to classify an independent phosphoserine/threonine data set with AUC value of 93% and PPV of 91%, demonstrating the applicability of this method for all types of phospho-MS/MS data. PhoMSVal is available at http://csbi.ltdk.helsinki.fi/phomsval., National Science Foundation (U.S.). Graduate Research Fellowship Program

Correlated variables have been shown to confound statistical analyses in microarray experiments. The same effect applies to an even greater degree in proteomics, especially with the use of MS for parallel measurements. Biological effects such as PTM, fragmentation, and multimer formation can produce strongly correlated variables. The problem is compounded in some types of MS by technical effects such as incomplete chromatographic separation, binding to multiple surfaces, or multiple ionizations. Existing methods for dimension reduction, notably principal components analysis and related techniques, are not always satisfactory because they produce data that often lack clear biological interpretation. We propose a preprocessing algorithm that clusters highly correlated features, using the Bayes information criterion to select an optimal number of clusters. Statistical analysis of clusters, instead of individual features, benefits from lower noise, and reduces the difficulties associated with strongly correlated data. This preprocessing increases the statistical power of analyses using false discovery rate on simulated data. Strong correlations are often present in real data, and we find that clustering improves biomarker discovery in clinical SELDI-TOF-MS datasets of plasma from patients with Kawasaki disease, and bone-marrow cell extracts from patients with acute myeloid or acute lymphoblastic leukemia.

The lysine methyltransferase (KMT) SETMAR is implicated in the response to and repair of DNA damage, but its molecular function is not clear. SETMAR has been associated with dimethylation of histone H3 lysine 36 (H3K36) at sites of DNA damage. However, SETMAR does not methylate H3K36 in vitro. This and the observation that SETMAR is not active on nucleosomes suggest that H3K36 methylation is not a physiologically relevant activity. To identify potential non-histone substrates, we utilized a strategy on the basis of quantitative proteomic analysis of methylated lysine. Our approach identified lysine 130 of the mRNA splicing factor snRNP70 as a SETMAR substrate in vitro, and we show that the enzyme primarily generates monomethylation at this position. Furthermore, we show that SETMAR methylates snRNP70 Lys-130 in cells. Because snRNP70 is a key early regulator of 5′ splice site selection, our results suggest a model in which methylation of snRNP70 by SETMAR regulates constitutive and/or alternative splicing. In addition, the proteomic strategy described here is broadly applicable and is a promising route for large-scale mapping of KMT substrates. Background: SETMAR is a lysine methyltransferase (KMT) that contributes to DNA repair, but its biochemical function is not well understood. Results: A novel proteomic strategy identifies splicing factor snRNP70 as a SETMAR substrate. Conclusion: SETMAR is the first KMT identified to target splicing factors. Significance: Proteomics can be harnessed to discover methyltransferase substrates. Lysine methylation may be a new mode of regulation for mRNA splicing.

Discovering valid biological information from surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) depends on clear experimental design, meticulous sample handling, and sophisticated data processing. Most published literature deals with the biological aspects of these experiments, or with computer-learning algorithms to locate sets of classifying biomarkers. The process of locating and measuring proteins across spectra has received less attention. This process should be tunable between sensitivity and false-discovery, and should guarantee that features are biologically meaningful in that they represent chemical species that can be identified and investigated. Existing feature detection in SELDI-TOF MS is not optimal for acquiring biologically relevant data. Most methods have so many user-defined settings that reproducibility and comparability among studies suffer considerably. To address these issues, we have developed an approach, called simultaneous spectrum analysis (SSA), which (i) locates proteins across spectra, (ii) measures their abundance, (iii) subtracts baseline, (iv) excludes irreproducible measurements, and (v) computes normalization factors for comparing spectra. SSA uses only two key parameters for feature detection and one parameter each for quality thresholds on spectra and peaks. The effectiveness of SSA is demonstrated by identifying proteins differentially expressed in SELDI-TOF spectra from plasma of wild-type and knockout mice for plasma glutathione peroxidase. Comparing analyses by SSA and CiphergenExpress Data Manager 2.1 finds similar results for large signal peaks, but SSA improves the number and quality of differences betweens groups among lower signal peaks. SSA is also less likely to introduce systematic bias when normalizing spectra.

We present a protocol for using the triple malignant brain tumor domains of L3MBTL1 (3xMBT), which bind to mono- and di-methylated lysine with minimal sequence specificity, in order to enrich for such methylated lysine from cell lysates. Cells in culture are grown with amino acids containing light or heavy stable isotopic labels. Methylated proteins are enriched by incubating cell lysates with 3xMBT, or with the binding-null D355N mutant as a negative control. Quantitative liquid chromatography and tandem mass spectrometry (LC-MS/MS) are then used to identify proteins that are specifically enriched by 3xMBT pull-down. The addition of a third isotopic label allows the comparison of protein lysine methylation between different biological conditions. Unlike most approaches, our strategy does not require a prior hypothesis of candidate methylated proteins, and it recognizes a wider range of methylated proteins than any available method using antibodies. Cells are prepared by growing in isotopic labeling medium for about 7 d; the process of enriching methylated proteins takes 3 d and analysis by LC-MS/MS takes another 1–2 d.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal form of cancer with few therapeutic options. We find that levels of the lysine methyltransferase SMYD2 are elevated in precancerous lesions and PDAC and that SMYD2 normally promotes Ras-driven development of PDAC. Notably, loss of SMYD2 correlates with diminished inflammation in PDAC and we identify the stress-response kinase MAPKAPK3 as a new and physiologically relevant SMYD2 substrate. Inhibition of MAPKAPK3 impedes PDAC growth, identifying a potential new kinase target in PDAC. Finally, we show that inhibition of SMYD2 cooperates with standard chemotherapy to treat PDAC cells and tumors. Together, our findings suggest new roles for SMYD2 in inflammation and stress responses, and identify SMYD2 and MAPKAPK3 as potential therapeutic targets to treat pancreatic cancer. Citation Format: Pawel K. Mazur, Nicolas Reynoird, Timo Stellfeld, Natasha M. Flores, Shane M. Lofgren, Scott M. Carlson, Elisabeth Brambilla, Pierre Hainaut, Ewa B. Kaznowska, Cheryl H. Arrowsmith, Purvesh Khatri, Carlo Stresemann, Or Gozani, Julien Sage.{Authors}. Coordination of stress signals by the lysine methyltransferase SMYD2 promotes pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr A44.

Proteins are regulated by an incredible array of posttranslational modifications (PTMs). Methylation of lysine residues on histone proteins is a PTM with well-established roles in regulating chromatin and epigenetic processes. The recent discovery that hundreds and likely thousands of nonhistone proteins are also methylated at lysine has opened a tremendous new area of research. Major cellular pathways involved in cancer, such as growth signaling and the DNA damage response, are regulated by lysine methylation. Although the field has developed quickly in recent years many fundamental questions remain to be addressed. We review the history and molecular functions of lysine methylation. We then discuss the enzymes that catalyze methylation of lysine residues, the enzymes that remove lysine methylation, and the cancer pathways known to be regulated by lysine methylation. The rest of the article focuses on two open questions that we suggest as a roadmap for future research. First is understanding the large number of candidate methyltransferase and demethylation enzymes whose enzymatic activity is not yet defined and which are potentially associated with cancer through genetic studies. Second is investigating the biological processes and cancer mechanisms potentially regulated by the multitude of lysine methylation sites that have been recently discovered.

Identifying kinase substrates is an important step in mapping signal transduction pathways, but it remains a difficult and time-consuming process. Analog-sensitive (AS) kinases have been used to selectively tag and identify direct kinase substrates in lysates from whole cells. In this approach, a γ-thiol adenosine triphosphate analog and an AS kinase are used to selectively thiophosphorylate target proteins. Thiophosphate is used as a chemical handle to purify peptides from a tryptic digest, and target proteins are identified by liquid chromatography and tandem mass spectrometry (LC-MS/MS). Here, we describe an updated strategy for labeling AS kinase substrates, solid-phase capture of thiophosphorylated peptides, incorporation of stable isotope labeling in cell culture for filtering nonspecific background peptides, enrichment of phosphorylated target peptides to identify low-abundance targets, and analysis by LC-MS/MS.

Chemical genetics represents an expanding collection of techniques applied to a variety of signaling processes. These techniques use a combination of chemical reporters and protein engineering to identify targets of a signaling enzyme in a global and non-directed manner without resorting to hypothesis-driven candidate approaches. In the last year, chemical genetics has been applied to a variety of kinases, revealing a much broader spectrum of substrates than had been appreciated. Here, we discuss recent developments in chemical genetics, including insights from our own proteomic screen for substrates of the kinase ERK2. These studies have revealed that many kinases have overlapping substrate specificity, and they often target several proteins in any particular downstream pathway. It remains to be determined whether this configuration exists to provide redundant control, or whether each target contributes a fraction of the total regulatory effect. From a general perspective, chemical genetics is applicable in principle to a broad range of posttranslational modifications (PTMs), most notably methylation and acetylation, although many challenges remain in implementing this approach. Recent developments in chemical reporters and protein engineering suggest that chemical genetics will soon be a powerful tool for mapping signal transduction through these and other PTMs.

The mitogen-activated protein kinase (MAPK) extracellular signal–regulated kinase 2 (ERK2) is ubiquitously expressed in mammalian tissues and is involved in a wide range of biological processes. Although MAPKs have been intensely studied, identification of their substrates remains challenging. We have optimized a chemical genetic system using analog-sensitive ERK2, a form of ERK2 engineered to use an analog of adenosine 5′-triphosphate (ATP), to tag and isolate ERK2 substrates in vitro. This approach identified 80 proteins phosphorylated by ERK2, 13 of which are known ERK2 substrates. The 80 substrates are associated with diverse cellular processes, including regulation of transcription and translation, mRNA processing, and regulation of the activity of the Rho family guanosine triphosphatases. We found that one of the newly identified substrates, ETV3 (a member of the E twenty-six family of transcriptional regulators), was extensively phosphorylated on sites within canonical and noncanonical ERK motifs. Phosphorylation of ETV3 regulated transcription by preventing its binding to DNA at promoters for several thousand genes, including some involved in negative feedback regulation of itself and of upstream signals., Massachusetts Institute of Technology (Eugene Bell Career Development Chair), David H. Koch Institute for Integrative Cancer Research at MIT (Graduate Fellowship), Massachusetts Institute of Technology (Whitaker Health Science Fellowship), National Science Foundation (U.S.) (Graduate Research Fellowship), Pfizer Inc., National Institutes of Health (U.S.) (grant ES002109), National Institutes of Health (U.S.) (grant R01DK42816), National Institutes of Health (U.S.) (grant R01CA118705), National Institutes of Health (U.S.) (grant U54CA112967)

The Department of Defense in many ways - and for many reasons - was not ready to fight and win during Operation Iraqi Freedom. The United States military didn't have the training, the procedures, or the proper resources to fight a counterinsurgency-type war. Still structured and resourced for conventional war, the Department of Defense (DoD) must change the course of its current transformation strategy or continue its poor record of dealing with terrorism and counterinsurgency. This paper will suggest two critical transformational changes required to maintain our military superiority. The most desperately-needed change is revamping the military personnel system to improve the way strategic leaders are developed. The second is developing an agency within the DoD that can fill the current void between military operations that defeat an enemy nation-state and assistance with the reconstruction of that society afterward. Without change, we can expect more situations like post-war Iraq, where in a country of 26 million people, conditions have deteriorated into an insurgency mixed with sectarian violence and where achieving a lasting victory with a predominantly military solution is proving not realistic or possible.

Preterm infants are at risk of developing sepsis, necrotizing enterocolitis (NEC), chronic lung disease (CLD), and retinopathy of prematurity (ROP). We used high-throughput mass spectrometry to investigate whether cord blood proteins can be used to predict development of these morbidities. Cord blood plasma from 44 infants with a birth weight of1500 g was analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF). Six infants developed ROPor=stage II, 10 CLD, three sepsis, and one NEC. We detected 814 protein signals representing 330 distinct protein species. Nineteen biomarkers were associated with development ofor=stage II ROP [false-discovery rate (FDR)5%] and none with CLD. Several proteins with molecular weight (Mr) 15-16 kD and pI 4-5 were detected with increased abundance in infants with ROP, while similar Mr proteins with pI 7-9 were less abundant in these patients. Sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and sequence analysis identified these proteins as alpha-, beta-, and gamma-globin chains. Partial deamidation of Asn139 in beta-globin chains was observed only in the pI 4-5 proteins. We conclude that there are several promising biomarkers for the risk of ROP. Deamidation of globin chains is especially promising and may indicate underlying prenatal pathologic mechanisms in ROP. Validation studies will be undertaken to determine their clinical utility.

We used molecular markers to study genetic relationships in a diverse collection of 85 domestic dog breeds. Differences among breeds accounted for ∼30% of genetic variation. Microsatellite genotypes were used to correctly assign 99% of individual dogs to breeds. Phylogenetic analysis separated several breeds with ancient origins from the remaining breeds with modern European origins. We identified four genetic clusters, which predominantly contained breeds with similar geographic origin, morphology, or role in human activities. These results provide a genetic classification of dog breeds and will aid studies of the genetics of phenotypic breed differences.

We present a joint linkage analysis of eight data sets collected for asthma. Three of the data sets are full genome scans, while the remaining five concentrate on a 40-cM region on chromosome 5. We perform the analysis using one qualitative and one quantitative phenotype: asthma status and IgE level. Considering all data sets simultaneously, we do not find evidence for linkage to asthma affection status beyond the level expected to occur by chance twice per genome scan. In contrast, we observe significant linkage to IgE level on chromosome 6.

The Education Forum by L. Bao et al. (“Learning and scientific reasoning,” 30 January, p. [586][1]) raises the question, why doesn't knowledge of scientific facts (in physics specifically) seem to correlate with skill in reasoning? I suspect that one factor is that American curricula generally emphasize a broad range of technical and nontechnical subjects, only one year of which is devoted to physics. Reasoning skills learned from these other subjects likely compensate for the dearth of physics, relative to that in Chinese schools. A second factor is probably the way in which science is taught. Science education in the United States is not focused on national college entrance exams (neither the SAT nor the ACT test factual science knowledge). Requirements and exams vary from state to state, but guidelines from the National Academy of Sciences emphasize reasoning over facts ([1][2]). Overall, educators have greater leeway to focus on reasoning and other less testable skills. Teaching American students more scientific knowledge is a laudable goal, but we should be careful about what gets sacrificed in the process. It is worth considering how much value most people will derive from advanced specific knowledge (Gauss's Law, for example) compared to broader background in a variety of subjects. Science education in the United States is woefully inadequate in many respects ([2][3]), and the number of failing schools is embarrassing. We must correct these failures but also remember what we've done right. The broad education characteristic of both K-12 and higher education in the United States has done an excellent job fostering creativity and innovation, measured by publications, patents, and growth in the science and technology work force ([2][3], [3][4]). We should work to improve scientific education by building on that success. 1. 1.[↵][5] 1. National Research Council , National Science Education Standards (National Academy Press, Washington, DC, 1996). 2. 2.[↵][6] 1. National Science Board , Science and Engineering Indicators 2008 (National Science Foundation, Arlington, VA, 2008) (chs. 3, 5, 7. 3. 3.[↵][7] 1. World Intellectual Property Organization , World Patent Report—A Statistical Review (2008) [www.wipo.int/freepublications/en/patents/931/wipo\_pub\_931_2008.pdf][8]. [1]: /lookup/doi/10.1126/science.1167740 [2]: #ref-1 [3]: #ref-2 [4]: #ref-3 [5]: #xref-ref-1-1 "View reference 1. in text" [6]: #xref-ref-2-1 "View reference 2. in text" [7]: #xref-ref-3-1 "View reference 3. in text" [8]: http://www.wipo.int/freepublications/en/patents/931/wipo_pub_931_2008.pdf