A family-based approach to preventing excessive weight gain

Objective: Preventing weight gain in adults and excessive weight gain in children is a high priority. We evaluated the ability of a family‐based program aimed at increasing steps and cereal consumption (for breakfast and snacks) to reduce weight gain in children and adults. Research Methods and Procedures: Families (n = 105) with at least one 8‐ to 12‐year‐old child who was at‐risk‐for‐overweight or overweight (designated as the target child) were recruited for the study. Eighty‐two families were randomly assigned to receive the family‐based intervention and 23 families to the control condition. The 13‐week intervention consisted of specific increases in daily steps (an additional 2000 steps/d) and consumption of 2 servings/d of ready‐to‐eat cereal. Results: The intervention was successful in increasing walking (steps) and cereal consumption. The intervention had positive, significant effects on percentage BMI‐for‐age and percentage body fat for target children and weight, BMI, and percentage body fat for parents. On further analysis, the positive effects of the intervention were seen largely in target girls and moms, rather than in target boys and dads. Discussion: This family‐based weight gain prevention program based on small changes holds promise for reducing excessive weight gain in families and especially in growing overweight children.     

The CATH database: an extended protein family resource for structural and functional genomics

The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath_new) currently contains 34 287 domain structures classified into 1383 superfamilies and 3285 sequence families. Each structural family is expanded with domain sequence relatives recruited from GenBank using a variety of efficient sequence search protocols and reliable thresholds. This extended resource, known as the CATH-protein family database (CATH-PFDB) contains a total of 310 000 domain sequences classified into 26 812 sequence families. New sequence search protocols have been designed, based on these intermediate sequence libraries, to allow more regular updating of the classification. Further developments include the adaptation of a recently developed method for rapid structure comparison, based on secondary structure matching, for domain boundary assignment. The philosophy behind CATHEDRAL is the recognition of recurrent folds already classified in CATH. Benchmarking of CATHEDRAL, using manually validated domain assignments, demonstrated that 43% of domains boundaries could be completely automatically assigned. This is an improvement on a previous consensus approach for which only 10-20% of domains could be reliably processed in a completely automated fashion. Since domain boundary assignment is a significant bottleneck in the classification of new structures, CATHEDRAL will also help to increase the frequency of CATH updates.     

A comparison of sequence and structure protein domain families as a basis for structural genomics.

MOTIVATION: Protein families can be defined based on structure or sequence similarity. We wanted to compare two protein family databases, one based on structural and one on sequence similarity, to investigate to what extent they overlap, the similarity in definition of corresponding families, and to create a list of large protein families with unknown structure as a resource for structural genomics. We also wanted to increase the sensitivity of fold assignment by exploiting protein family HMMs. RESULTS: We compared Pfam, a protein family database based on sequence similarity, to Scop, which is based on structural similarity. We found that 70% of the Scop families exist in Pfam while 57% of the Pfam families exist in Scop. Most families that occur in both databases correspond well to each other, but in some cases they are different. Such cases highlight situations in which structure and sequence approaches differ significantly. The comparison enabled us to compile a list of the largest families that do not occur in Scop; these are suitable targets for structure prediction and determination, and may be useful to guide projects in structural genomics. It can be noted that 13 out of the 20 largest protein families without a known structure are likely transmembrane proteins. We also exploited Pfam to increase the sensitivity of detecting homologs of proteins with known structure, by comparing query sequences to Pfam HMMs that correspond to Scop families. For SWISSPROT+TREMBL, this yielded an increase in fold assignment from 31% to 42% compared to using FASTA only. This method assigned a structure to 22% of the proteins in Saccharomyces cerevisiae, 24% in Escherichia coli, and 16% in Methanococcus jannaschii.     

Correlated mutation analyses on super‐family alignments reveal functionally important residues

Correlated mutation analyses (CMA) on multiple sequence alignments are widely used for the prediction of the function of amino acids. The accuracy of CMA‐based predictions is mainly determined by the number of sequences, by their evolutionary distances, and by the quality of the alignments. These criteria are best met in structure‐based sequence alignments of large super‐families. So far, CMA‐techniques have mainly been employed to study the receptor interactions. The present work shows how a novel CMA tool, called Comulator, can be used to determine networks of functionally related residues in enzymes. These analyses provide leads for protein engineering studies that are directed towards modification of enzyme specificity or activity. As proof of concept, Comulator has been applied to four enzyme super‐families: the isocitrate lyase/phoshoenol‐pyruvate mutase super‐family, the hexokinase super‐family, the RmlC‐like cupin super‐family, and the FAD‐linked oxidases super‐family. In each of those cases networks of functionally related residue positions were discovered that upon mutation influenced enzyme specificity and/or activity as predicted. We conclude that CMA is a powerful tool for redesigning enzyme activity and selectivity. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Identification of dipeptide repeats and a cell wall sorting signal in the fimbriae-associated adhesin, Fap1, of Streptococcus parasanguis

Fap1, a fimbriae-associated protein, is involved in fimbriae assembly and adhesion of Streptococcus parasanguis FW213 (Wu et al., 1998). In this study, the sequence of the fap1 gene was resolved using a primer island transposition system. Sequence analysis indicated that fap1 was composed of 7659 nucleotides. The predicted Fap1 protein contains an unusually long signal sequence (50 amino acid residues), a cell wall sorting signal and two repeat regions. Repeat regions I and II have a similar dipeptide composition (E/V/I)S, composed of 28 and 1000 repeats respectively. The two regions combined accounted for 80% of the Fap1 coding region. The experimental amino acid composition and isoelectric point (pI) of Fap1 were similar to that predicted from the deduced Fap1 protein. Results of Northern analyses revealed that the fap1 open reading frame (ORF) was transcribed as a 7.8 kb monocistronic message. Insertional inactivation at the 3' end, downstream of the fap1 ORF, did not affect Fap1, fimbrial expression or bacterial adhesion. Insertional inactivation of fap1 immediately upstream of the repeat region II abolished expression of Fap1 and fimbriae, and was concurrent with a diminution in adhesion of FW213. Inactivation of the cell wall sorting signal of fap1 also eliminated long fimbrial formation and reduced the ability of FW213 to bind to SHA. Fap1 was no longer anchored on the cell surface. Large quantities of truncated Fap1 were found in the growth medium instead. These results suggest that the fap1 ORF alone is sufficient to support Fap1 expression and adhesion, and demonstrate that anchorage of Fap1 on the cell surface is required for long fimbriae formation. These data further document the role of long fimbriae in adhesion of S. parasanguis FW213 to SHA.     

PCR‐based isolation of multigene families: lessons from the avian MHC class IIB

The amount of sequence data available today highly facilitates the access to genes from many gene families. Primers amplifying the desired genes over a range of species are readily obtained by aligning conserved gene regions, and laborious gene isolation procedures can often be replaced by quicker PCR‐based approaches. However, in the case of multigene families, PCR‐based approaches bear the often ignored risk of incomplete isolation of family members. This problem is most prominent in gene families with highly variable and thus unpredictable number of gene copies among species, such as in the major histocompatibility complex (MHC). In this study, we (i) report new primers for the isolation of the MHC class IIB (MHCIIB) gene family in birds and (ii) share our experience with isolating MHCIIB genes from an unprecedented number of avian species from all over the avian phylogeny. We report important and usually underappreciated problems encountered during PCR‐based multigene family isolation and provide a collection of measures to help significantly improving the chance of successfully isolating complete multigene families using PCR‐based approaches.     

Predicting functional family of novel enzymes irrespective of sequence similarity: a statistical learning approach

The function of a protein that has no sequence homolog of known function is difficult to assign on the basis of sequence similarity. The same problem may arise for homologous proteins of different functions if one is newly discovered and the other is the only known protein of similar sequence. It is desirable to explore methods that are not based on sequence similarity. One approach is to assign functional family of a protein to provide useful hint about its function. Several groups have employed a statistical learning method, support vector machines (SVMs), for predicting protein functional family directly from sequence irrespective of sequence similarity. These studies showed that SVM prediction accuracy is at a level useful for functional family assignment. But its capability for assignment of distantly related proteins and homologous proteins of different functions has not been critically and adequately assessed. Here SVM is tested for functional family assignment of two groups of enzymes. One consists of 50 enzymes that have no homolog of known function from PSI-BLAST search of protein databases. The other contains eight pairs of homologous enzymes of different families. SVM correctly assigns 72% of the enzymes in the first group and 62% of the enzyme pairs in the second group, suggesting that it is potentially useful for facilitating functional study of novel proteins. A web version of our software, SVMProt, is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.     

A kinase sequence database: sequence alignments and family assignment

SUMMARY: The Kinase Sequence Database (KSD) located at http://kinase.ucsf.edu/ksd contains information on 290 protein kinase families derived by profile-based clustering of the non-redundant list of sequences obtained from a GenBank-wide search. Included in the database are a total of 5,041 protein kinases from over 100 organisms. Clustering into families is based on the extent of homology within the kinase catalytic domain (250-300 residues in length). Alignments of the families are viewed by interactive Excel-based sequence spreadsheets. In addition, KSD features evolutionary trees derived for each family and detailed information on each sequence as well as links to the corresponding GenBank entries. Sequence manipulation tools, such as evolutionary tree generation, novel sequence assignment, and statistical analysis, are also provided. AVAILABILITY: The kinase sequence database is a web-based service accessible at http://kinase.ucsf.edu/ksd CONTACT: buzko@cmp.ucsf.edu; shokat@cmp.ucsf.edu/ksd     

Protein families and TRIBES in genome sequence space

Accurate detection of protein families allows assignment of protein function and the analysis of functional diversity in complete genomes. Recently, we presented a novel algorithm called TribeMCL for the detection of protein families that is both accurate and efficient. This method allows family analysis to be carried out on a very large scale. Using TribeMCL, we have generated a resource called TRIBES that contains protein family information, comprising annotations, protein sequence alignments and phylogenetic distributions describing 311 257 proteins from 83 completely sequenced genomes. The analysis of at least 60 934 detected protein families reveals that, with the essential families excluded, paralogy levels are similar between prokaryotes, irrespective of genome size. The number of essential families is estimated to be between 366 and 426. We also show that the currently known space of protein families is scale free and discuss the implications of this distribution. In addition, we show that smaller families are often formed by shorter proteins and discuss the reasons for this intriguing pattern. Finally, we analyse the functional diversity of protein families in entire genome sequences. The TRIBES protein family resource is accessible at http://www.ebi.ac.uk/research/cgg/tribes/.     

Conservation of structural fluctuations in homologous protein kinases and its implications on functional sites

Our aim is to explore the similarities in structural fluctuations of homologous kinases. Gaussian Network Model based Normal Mode Analysis was performed on 73 active conformation structures in Ser/Thr/Tyr kinase superfamily. Categories of kinases with progressive evolutionary divergence, viz. (i) Same kinase with many crystal structures, (ii) Within‐Subfamily, (iii) Within‐Family, (iv) Within‐Group, and (v) Across‐Group, were analyzed. We identified a flexibility signature conserved in all kinases involving residues in and around the catalytic loop with consistent low‐magnitude fluctuations. However, the overall structural fluctuation profiles are conserved better in closely related kinases (Within‐Subfamily and Within‐family) than in distant ones (Within‐Group and Across‐Group). A substantial 65.4% of variation in flexibility was not accounted by variation in sequences or structures. Interestingly, we identified substructural residue‐wise fluctuation patterns characteristic of kinases of different categories. Specifically, we recognized statistically significant fluctuations unique to families of protein kinase A, cyclin‐dependent kinases, and nonreceptor tyrosine kinases. These fluctuation signatures localized to sites known to participate in protein‐protein interactions typical of these kinase families. We report for the first time that residues characterized by fluctuations unique to the group/family are involved in interactions specific to the group/family. As highlighted for Src family, local regions with differential fluctuations are proposed as attractive targets for drug design. Overall, our study underscores the importance of consideration of fluctuations, over and above sequence and structural features, in understanding the roles of sites characteristic of kinases. Proteins 2016; 84:957–978. © 2016 Wiley Periodicals, Inc.     

Genetic variation in variability: Phenotypic variability of fledging weight and its evolution in a songbird population

Variation in traits is essential for natural selection to operate and genetic and environmental effects can contribute to this phenotypic variation. From domesticated populations, we know that families can differ in their level of within‐family variance, which leads to the intriguing situation that within‐family variance can be heritable. For offspring traits, such as birth weight, this implies that within‐family variance in traits can vary among families and can thus be shaped by natural selection. Empirical evidence for this in wild populations is however lacking. We investigated whether within‐family variance in fledging weight is heritable in a wild great tit (Parus major) population and whether these differences are associated with fitness. We found significant evidence for genetic variance in within‐family variance. The genetic coefficient of variation (GCV) was 0.18 and 0.25, when considering fledging weight a parental or offspring trait, respectively. We found a significant quadratic relationship between within‐family variance and fitness: families with low or high within‐family variance had lower fitness than families with intermediate within‐family variance. Our results show that within‐family variance can respond to selection and provides evidence for stabilizing selection on within‐family variance.     

Phylogenetics and evolution of Capitata (Cnidaria: Hydrozoa), and the systematics of Corynidae

Nawrocki, A. M., Schuchert, P. & Cartwright, P. (2009). Phylogenetics and evolution of Capitata (Cnidaria: Hydrozoa), and the systematics of Corynidae.—Zoologica Scripta, 39, 290–304. Generic‐ and family level classifications in Hydrozoa have been historically problematic due to limited morphological characters for phylogenetic analyses and thus taxonomy, as well as disagreement over the relative importance of polyp vs. medusa characters. Within the recently redefined suborder Capitata (Cnidaria: Hydrozoa: Hydroidolina), which includes 15 families and almost 200 valid species, family level relationships based on morphology alone have proven elusive, and there exist numerous conflicting proposals for the relationships of component species. Relationships within the speciose capitate family Corynidae also remain uncertain, for similar reasons. Here, we combine mitochondrial 16S, and nuclear 18S and 28S sequences from capitate hydrozoans representing 12 of the 15 valid capitate families, to examine family level relationships within Capitata. We further sample densely within Corynidae to investigate the validity of several generic‐level classification schemes that rely heavily on the presence/absence of a medusa, a character that has been questioned for its utility in generic‐level classification. We recover largely congruent tree topologies from all three markers, with 28S and the combined dataset providing the most resolution. Our study confirms the monophyly of the redefined Capitata, and provides resolution for family level relationships of most sampled families within the suborder. These analyses reveal Corynidae as paraphyletic and suggest that the limits of the family have been underestimated. Our results contradict all available generic‐level classification schemes for Corynidae. As classification schemes for this family have been largely based on reproductive characters such as the presence/absence of a medusa, our results suggest that these are not valid generic‐level characters for the clade. We suggest a new taxonomic structure for the lineage that includes all members of the newly redefined Corynidae, based on molecular and morphological synapomorphies for recovered clades within the group.     

Identification of the molecular genetic basis of the low palmitic acid seed oil trait in soybean mutant line RG3 and association analysis of molecular markers with elevated seed stearic acid and reduced seed palmitic acid

The fatty acid composition of vegetable oil is becoming increasingly critical for its ultimate functionality and utilization in foods and industrial products. Partial chemical hydrogenation of soybean [Glycine max (L.) Merr.] oil increases oxidative stability and shelf life but also results in the introduction of trans fats as an unavoidable byproduct. Due to mandatory labeling of consumer products containing trans fats, conventional soybean oil has lost the ability to deliver the most appropriate economical functionality and oxidative stability, particularly for baking applications. Genetic improvement of the fatty acid profile of soybean oil is one method of meeting these new requirements for oil feedstocks. In this report, we characterized three mutant genetic loci controlling the saturated fatty acid content of soybean oil: two genes additively reduce palmitic acid content (fap1 and fap3-ug), and one gene independently elevates stearic acid content (fas). We identified a new null allele of fap3-ug/GmFATB1A (derived from line ELLP2) present in line RG3. The splicing defect mutation in a beta-ketoacyl-[acyl-carrier-protein] synthase III candidate gene located in the region mapped to fap1, derived originally from ethyl methane sulphonate mutant line C1726 (Cardinal et al. in Theor Appl Genet 127:97–111, 2014), was also present in line RG3. We also utilized the elevated stearic acid line RG7, which has previously been shown to contain novel mutant fas/SACPD-C alleles encoding stearoyl-acyl carrier protein desaturase (Boersma et al. in Crop Sci 52:1736–1742, 2012). Molecular marker assays have been developed to track these causative mutations and understand their contributions to seed oil fatty acid profiles in a recombinant inbred line population segregating for fap1, fap3-ug, and fas alleles.     

Recognition of remotely related structural homologues using sequence profiles of aligned homologous protein structures

In order to bridge the gap between proteins with three-dimensional (3-D) structural information and those without 3-D structures, extensive experimental and computational efforts for structure recognition are being invested. One of the rapid and simple computational approaches for structure recognition makes use of sequence profiles with sensitive profile matching procedures to identify remotely related homologous families. While adopting this approach we used profiles that are generated from structure-based sequence alignment of homologous protein domains of known structures integrated with sequence homologues. We present an assessment of this fast and simple approach. About one year ago, using this approach, we had identified structural homologues for 315 sequence families, which were not known to have any 3-D structural information. The subsequent experimental structure determination for at least one of the members in 110 of 315 sequence families allowed a retrospective assessment of the correctness of structure recognition. We demonstrate that correct folds are detected with an accuracy of 96.4% (106/110). Most (81/106) of the associations are made correctly to the specific structural family. For 23/106, the structure associations are valid at the superfamily level. Thus, profiles of protein families of known structure when used with sensitive profile-based search procedure result in structure association of high confidence. Further assignment at the level of superfamily or family would provide clues to probable functions of new proteins. Importantly, the public availability of these profiles from us could enable one to perform genome wide structure assignment in a local machine in a fast and accurate manner.     

Infantile hypophosphatasia: localization within chromosome region 1p36.1-34 and prenatal diagnosis using linked DNA markers.

Linkage analysis was performed on data from Manitoba Mennonite families identified by a proband with infantile hypophosphatasia (HOPS), an autosomal recessive disorder characterized by defective skeletal mineralization. Southern blot analysis of Msp-I-digested DNA from HOPS nuclear families probed with a 2.55-kb liver/bone/kidney alkaline phosphatase (ALPL) cDNA revealed two previously undescribed RFLPs at 2.4/2.3 kb and 2.0/1.9 kb. Maximum combined lod score equals 13.25 at theta = 0. This establishes very close linkage between ALPL and HOPS and allows for the regional assignment of the HOPS gene to chromosome 1p36.1-34. Prenatal RFLP studies in an informative Mennonite family correctly predicted an unaffected fetus following chorionic villus sampling at 12 wk gestation. In addition in our Mennonite population, a nonrandom association exists between the polymorphic ALPL alleles and HOPS. These results suggest that strong linkage disequilibrium exists between HOPS and the ALPL markers. This will allow for improved carrier assignment in this high-risk population. Preliminary analysis suggests approximately 1/25 Manitoba Mennonites are HOPS carriers.     

The genetics of affective disorder and genetic counseling

Abstract

Affective disorders—depression and mania—occurring with no preexisting psychiatric condition, severe physical illness, or recent personal loss can be divided into unipolar (depression only) and bipolar (both manic and depressive episodes) disorders. Bipolar illness is transmitted in some families as an X‐linked dominant factor. In other families, X‐linked transmission does not occur. Hence, bipolar illness may be similar to retinitis pigmentosa. This makes some types of genetic counseling difficult to apply to bipolar families. There is no evidence that unipolar depressive illness is transmitted by an X‐linked factor. Family studies indicate that there might be more than one type of unipolar illness. Limited prediction of risk of depression and other psychiatric conditions in other family members can be based on family studies which show that alcoholism and personality disorder occur frequently in families of early onset depressives but much less frequently in families of late onset depressives (age 40 or older).     

An efficient algorithm for large-scale detection of protein families

Detection of protein families in large databases is one of the principal research objectives in structural and functional genomics. Protein family classification can significantly contribute to the delineation of functional diversity of homologous proteins, the prediction of function based on domain architecture or the presence of sequence motifs as well as comparative genomics, providing valuable evolutionary insights. We present a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families. The method relies on the Markov cluster (MCL) algorithm for the assignment of proteins into families based on precomputed sequence similarity information. This novel approach does not suffer from the problems that normally hinder other protein sequence clustering algorithms, such as the presence of multi-domain proteins, promiscuous domains and fragmented proteins. The method has been rigorously tested and validated on a number of very large databases, including SwissProt, InterPro, SCOP and the draft human genome. Our results indicate that the method is ideally suited to the rapid and accurate detection of protein families on a large scale. The method has been used to detect and categorise protein families within the draft human genome and the resulting families have been used to annotate a large proportion of human proteins.