The transporter classification (TC) system, 2002

The Transporter Classification (TC) system is a functional/phylogenetic system designed for the classification of all transmembrane transport proteins found in living organisms on Earth. It parallels but differs from the strictly functional EC system developed decades ago by the Enzyme Commission of the International Union of Biochemistry and Molecular Biology (IUBMB) for the classification of enzymes. Recently, the TC system has been adopted by the IUBMB as the internationally acclaimed system for the classification of transporters. Here we present the characteristics of the nearly 400 families of transport systems included in the TC system and provide statistical analyses of these families and their constituent proteins. Specifically, we analyze the transporter types for size and topological differences and analyze the families for the numbers and organismal sources of their constituent members. We show that channels and carriers exhibit distinctive structural and topological features. Bacterial-specific families outnumber eukaryotic-specific families about 2 to 1, while ubiquitous families, found in all three domains of life, are about half as numerous as eukaryotic-specific families. The results argue against appreciable horizontal transfer of genes encoding transporters between the three domains of life over the last 2 billion years.     

A functional-phylogenetic classification system for transmembrane solute transporters.

A comprehensive classification system for transmembrane molecular transporters has been developed and recently approved by the transport panel of the nomenclature committee of the International Union of Biochemistry and Molecular Biology. This system is based on (i) transporter class and subclass (mode of transport and energy coupling mechanism), (ii) protein phylogenetic family and subfamily, and (iii) substrate specificity. Almost all of the more than 250 identified families of transporters include members that function exclusively in transport. Channels (115 families), secondary active transporters (uniporters, symporters, and antiporters) (78 families), primary active transporters (23 families), group translocators (6 families), and transport proteins of ill-defined function or of unknown mechanism (51 families) constitute distinct categories. Transport mode and energy coupling prove to be relatively immutable characteristics and therefore provide primary bases for classification. Phylogenetic grouping reflects structure, function, mechanism, and often substrate specificity and therefore provides a reliable secondary basis for classification. Substrate specificity and polarity of transport prove to be more readily altered during evolutionary history and therefore provide a tertiary basis for classification. With very few exceptions, a phylogenetic family of transporters includes members that function by a single transport mode and energy coupling mechanism, although a variety of substrates may be transported, sometimes with either inwardly or outwardly directed polarity. In this review, I provide cross-referencing of well-characterized constituent transporters according to (i) transport mode, (ii) energy coupling mechanism, (iii) phylogenetic grouping, and (iv) substrates transported. The structural features and distribution of recognized family members throughout the living world are also evaluated. The tabulations should facilitate familial and functional assignments of newly sequenced transport proteins that will result from future genome sequencing projects.     

Prediction of transporter family from protein sequence by support vector machine approach

Transporters play key roles in cellular transport and metabolic processes, and in facilitating drug delivery and excretion. These proteins are classified into families based on the transporter classification (TC) system. Determination of the TC family of transporters facilitates the study of their cellular and pharmacological functions. Methods for predicting TC family without sequence alignments or clustering are particularly useful for studying novel transporters whose function cannot be determined by sequence similarity. This work explores the use of a machine learning method, support vector machines (SVMs), for predicting the family of transporters from their sequence without the use of sequence similarity. A total of 10,636 transporters in 13 TC subclasses, 1914 transporters in eight TC families, and 168,341 nontransporter proteins are used to train and test the SVM prediction system. Testing results by using a separate set of 4351 transporters and 83,151 nontransporter proteins show that the overall accuracy for predicting members of these TC subclasses and families is 83.4% and 88.0%, respectively, and that of nonmembers is 99.3% and 96.6%, respectively. The accuracies for predicting members and nonmembers of individual TC subclasses are in the range of 70.7-96.1% and 97.6-99.9%, respectively, and those of individual TC families are in the range of 60.6-97.1% and 91.5-99.4%, respectively. A further test by using 26,139 transmembrane proteins outside each of the 13 TC subclasses shows that 90.4-99.6% of these are correctly predicted. Our study suggests that the SVM is potentially useful for facilitating functional study of transporters irrespective of sequence similarity.     

Phylogenetic classification of transporters and other membrane proteins from Saccharomyces cerevisiae

On the basis of functional and phylogenetic criteria, we have identified a total of 229 subfamilies and 111 singletons predicted to carry out transport or other membrane functions in Saccharomyces cerevisiae. We have extended the Transporter Classification (TC) and created a Membrane Classification (MC) for non-transporter membrane proteins. Using the preliminary phylogenetic digits X, Y, Z (for new families, subfamilies, and clusters, respectively), we allocated a five-digit number to 850 proteins predicted to contain more than two transmembrane domains. Compared with a previous TC of the yeast genome, we classified an additional set of 538 membrane proteins (transporters and non-transporters) and identified 111 novel phylogenetic subfamilies. Electronic Publication     

Tracing pathways of transport protein evolution

We have conducted bioinformatic analyses of integral membrane transport proteins belonging to dozens of families. These families rarely include proteins that function in a capacity other than transport. Many transporters have arisen by intragenic duplication, triplication and quadruplication events, in which the numbers of transmembrane alpha-helical hydrophobic segments (TMSs) have increased. The elements multiplied may encode two, three, four, five, six, 10 or 12 TMSs and gave rise to proteins with four, six, seven, eight, nine, 10, 12, 20, 24 and 30 TMSs. Gene fusion, splicing, deletion and insertion events have also contributed to protein topological diversity. Amino acid substitutions have allowed membrane-embedded domains to become hydrophilic domains and vice versa. Some evidence suggests that amino acid substitutions occurring over evolutionary time may in some cases have drastically altered protein topology. The results summarized in this microreview establish the independent origins of many transporter families and allow postulation of the specific pathways taken for their appearance.     

Enzyme family classification by support vector machines

One approach for facilitating protein function prediction is to classify proteins into functional families. Recent studies on the classification of G-protein coupled receptors and other proteins suggest that a statistical learning method, Support vector machines (SVM), may be potentially useful for protein classification into functional families. In this work, SVM is applied and tested on the classification of enzymes into functional families defined by the Enzyme Nomenclature Committee of IUBMB. SVM classification system for each family is trained from representative enzymes of that family and seed proteins of Pfam curated protein families. The classification accuracy for enzymes from 46 families and for non-enzymes is in the range of 50.0% to 95.7% and 79.0% to 100% respectively. The corresponding Matthews correlation coefficient is in the range of 54.1% to 96.1%. Moreover, 80.3% of the 8,291 correctly classified enzymes are uniquely classified into a specific enzyme family by using a scoring function, indicating that SVM may have certain level of unique prediction capability. Testing results also suggest that SVM in some cases is capable of classification of distantly related enzymes and homologous enzymes of different functions. Effort is being made to use a more comprehensive set of enzymes as training sets and to incorporate multi-class SVM classification systems to further enhance the unique prediction accuracy. Our results suggest the potential of SVM for enzyme family classification and for facilitating protein function prediction. Our software is accessible at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.     

Membrane topology screen of secondary transport proteins in structural class ST[3] of the MemGen classification. Confirmation and structural diversity

The MemGen structural classification of membrane proteins groups families of proteins by hydropathy profile alignment. Class ST[3] of the MemGen classification contains 32 families of transporter proteins including the IT superfamily. Transporters from 19 different families in class ST[3] were evaluated by the TopScreen experimental topology screening method to verify the structural classification by MemGen. TopScreen involves the determination of the cellular disposition of three sites in the polypeptide chain of the proteins which allows for discrimination between different topology models. For nearly all transporters at least one of the predicted localizations is different in the models produced by MemGen and predictor TMHMM. Comparison to the experimental data showed that in all cases the prediction by MemGen was correct. It is concluded that the structural model available for transporters of the [st324]ESS and [st326]2HCT families is also valid for the other families in class ST[3]. The core structure of the model consists of two homologous domains, each containing 5 transmembrane segments, which have an opposite orientation in the membrane. A reentrant loop is present in between the 4th and 5th segments in each domain. Nearly all of the identified and experimentally confirmed structural variations involve additions of transmembrane segments at the boundaries of the core model, at the N- and C-termini or in between the two domains. Most remarkable is a domain swap in two subfamilies of the [st312]NHAC family that results in an inverted orientation of the proteins in the membrane.     

The drug/metabolite transporter superfamily.

Previous work defined several families of secondary active transporters, including the prokaryotic small multidrug resistance (SMR) and rhamnose transporter (RhaT) families as well as the eukaryotic organellar triose phosphate transporter (TPT) and nucleotide-sugar transporter (NST) families. We show that these families as well as several other previously unrecognized families of established or putative secondary active transporters comprise a large ubiquitous superfamily found in bacteria, archaea and eukaryotes. We have designated it the drug/metabolite transporter (DMT) superfamily (transporter classification number 2.A.7) and have shown that it consists of 14 phylogenetic families, five of which include no functionally well-characterized members. The largest family in the DMT superfamily, the drug/metabolite exporter (DME) family, consists of over 100 sequenced members, several of which have been implicated in metabolite export. Each DMT family consists of proteins with a distinctive topology: four, five, nine or 10 putative transmembrane alpha helical spanners (TMSs) per polypeptide chain. The five TMS proteins include an N-terminal TMS lacking the four TMS proteins. The full-length proteins of 10 putative TMSs apparently arose by intragenic duplication of an element encoding a primordial five-TMS polypeptide. Sequenced members of the 14 families are tabulated and phylogenetic trees for all the families are presented. Sequence and topological analyses allow structural and functional predictions.     

The bile/arsenite/riboflavin transporter (BART) superfamily

Secondary transmembrane transport carriers fall into families and superfamilies allowing prediction of structure and function. Here we describe hundreds of sequenced homologues that belong to six families within a novel superfamily, the bile/arsenite/riboflavin transporter (BART) superfamily, of transport systems and putative signalling proteins. Functional data for members of three of these families are available, and they transport bile salts and other organic anions, the bile acid:Na(+) symporter (BASS) family, inorganic anions such as arsenite and antimonite, the arsenical resistance-3 (Acr3) family, and the riboflavin transporter (RFT) family. The first two of these families, as well as one more family with no functionally characterized members, exhibit a probable 10 transmembrane spanner (TMS) topology that arose from a tandemly duplicated 5 TMS unit. Members of the RFT family have a 5 TMS topology, and are homologous to each of the repeat units in the 10 TMS proteins. The other two families [sensor histidine kinase (SHK) and kinase/phosphatase/synthetase/hydrolase (KPSH)] have a single 5 TMS unit preceded by an N-terminal TMS and followed by a hydrophilic sensor histidine kinase domain (the SHK family) or catalytic domains resembling sensor kinase, phosphatase, cyclic di-GMP synthetase and cyclic di-GMP hydrolase catalytic domains, as well as various noncatalytic domains (the KPSH family). Because functional data are not available for members of the SHK and KPSH families, it is not known if the transporter domains retain transport activity or have evolved exclusive functions in molecular reception and signal transmission. This report presents characteristics of a unique protein superfamily and provides guides for future studies concerning structural, functional and mechanistic properties of its constituent members.     

Microbial genome analyses: comparative transport capabilities in eighteen prokaryotes

Here, we present a comprehensive analysis of solute transport systems encoded within the completely sequenced genomes of 18 prokaryotic organisms. These organisms include four Gram-positive bacteria, seven Gram-negative bacteria, two spirochetes, one cyanobacterium and four archaea. Membrane proteins are analyzed in terms of putative membrane topology, and the recognized transport systems are classified into 76 families, including four families of channel proteins, four families of primary carriers, 54 families of secondary carriers, six families of group translocators, and eight unclassified families. These families are analyzed in terms of the paralogous and orthologous relationships of their protein members, the substrate specificities of their constituent transporters and their distributions in each of the 18 organisms studied. The families vary from large superfamilies with hundreds of represented members, to small families with only one or a few members. The mode of transport generally correlates with the primary mechanism of energy generation, and the numbers of secondary transporters relative to primary transporters are roughly proportional to the total numbers of primary H(+) and Na(+) pumps in the cell. The phosphotransferase system is less prevalent in the analyzed bacteria than previously thought (only six of 14 bacteria transport sugars via this system) and is completely lacking in archaea and eukaryotes. Escherichia coli is shown to be exceptionally broad in its transport capabilities and therefore, at a membrane transport level, does not appear representative of the bacteria thus far sequenced. Archaea and spirochetes exhibit fewer proteins with multiple transmembrane segments and fewer net transporters than most bacteria. These results provide insight into the relevance of transport to the overall physiology of prokaryotes.     

Evolution of gene families: the multidrug resistance transporter genes in five related yeast species

The available genomic sequences of five closely related hemiascomycetous yeast species (Kluyveromyces lactis, Kluyveromyces waltii, Candida glabrata, Ashbya (Eremothecium) gossypii with Saccharomyces cerevisiae as a reference) were analysed to identify multidrug resistance (MDR) transport proteins belonging to the ATP-binding cassette (ABC) and major facilitator superfamilies (MFS), respectively. The phylogenetic trees clearly demonstrate that a similar set of gene (sub)families already existed in the common ancestor of all five fungal species studied. However, striking differences exist between the two superfamilies with respect to the evolution of the various subfamilies. Within the ABC superfamily all six half-size transporters with six transmembrane-spanning domains (TMs) and most full-size transporters with 12 TMs have one and only one gene per genome. An exception is the PDR family, in which gene duplications and deletions have occurred independently in individual genomes. Among the MFS transporters, the DHA2 family (TC 2.A.1.3) is more variable between species than the DHA1 family (TC 2.A.1.2). Conserved gene order relationships allow to trace the evolution of most (sub)families, for which the Kluyveromyces lactis genome can serve as an optimal scaffold. Cross-species sequence alignment of orthologous upstream gene sequences led to the identification of conserved sequence motifs ("phylogenetic footprints"). Almost half of them match known sequence motifs for the MDR regulators described in S. cerevisiae. The biological significance of those and of the novel predicted motifs awaits to be confirmed experimentally.     

Functional and evolutionary analysis of viral proteins containing a Rossmann‐like fold

Viruses are the most abundant life form and infect practically all organisms. Consequently, these obligate parasites are a major cause of human suffering and economic loss. Rossmann‐like fold is the most populated fold among α/β‐folds in the Protein Data Bank and proteins containing Rossmann‐like fold constitute 22% of all known proteins 3D structures. Thus, analysis of viral proteins containing Rossmann‐like domains could provide an understanding of viral biology and evolution as well as could propose possible targets for antiviral therapy. We provide functional and evolutionary analysis of viral proteins containing a Rossmann‐like fold found in the evolutionary classification of protein domains (ECOD) database developed in our lab. We identified 81 protein families of bacterial, archeal, and eukaryotic viruses in light of their evolution‐based ECOD classification and Pfam taxonomy. We defined their functional significance using enzymatic EC number assignments as well as domain‐level family annotations.     

Families of twelve transmembrane domain transporters.

Several functionally distinct families of transport proteins share the general structural motif of twelve transmembrane domains. The number of membrane proteins known to possess this common feature continues to expand with the cloning of transporters for various neurotransmitters, nucleosides, osmolytes and basic amino acids, in addition to the previously defined families of facilitative and sodium-driven sugar transporters.     

The major facilitator superfamily (MFS) revisited

The major facilitator superfamily (MFS) is the largest known superfamily of secondary carriers found in the biosphere. It is ubiquitously distributed throughout virtually all currently recognized organismal phyla. This superfamily currently (2012) consists of 74 families, each of which is usually concerned with the transport of a certain type of substrate. Many of these families, defined phylogenetically, do not include even a single member that is functionally characterized. In this article, we probe the evolutionary origins of these transporters, providing evidence that they arose from a single 2-transmembrane segment (TMS) hairpin structure that triplicated to give a 6-TMS unit that duplicated to a 12-TMS protein, the most frequent topological type of these permeases. We globally examine MFS protein topologies, focusing on exceptional proteins that deviate from the norm. Nine distantly related families appear to have members with 14?TMSs in which the extra two are usually centrally localized between the two 6-TMS repeat units. They probably have arisen by intragenic duplication of an adjacent hairpin. This alternative topology probably arose multiple times during MFS evolution. Convincing evidence for MFS permeases with fewer than 12?TMSs was not forthcoming, leading to the suggestion that all 12?TMSs are required for optimal function. Some homologs appear to have 13, 14, 15 or 16 TMSs, and the probable locations of the extra TMSs were identified. A few MFS permeases are fused to other functional domains or are fully duplicated to give 24-TMS proteins with dual functions. Finally, the MFS families with no known function were subjected to genomic context analyses leading to functional predictions.     

高等植物K+吸收转运蛋白及其分子调节

K 在植物的生命活动中发挥着十分重要的作用。植物对K 的吸收,可分为高亲和吸收与低亲和吸收。在分子水平上,高亲和吸收主要由KUP/HAK/KT及HKT家族的K 转运蛋白来承担;而Shaker、KCO等家族的K 通道蛋白,则主要在植物的低亲和吸收中发挥重要作用。AKT1、HAK5及其在植物中的同源基因在高等植物K 吸收转运中占有举足轻重的地位。KUP/HAK/KT家族基因的调节,主要是转录水平的调节,而K 通道蛋白的调节则可能主要是一种翻译后调节。植物的蛋白激酶通过磷酸化K 通道蛋白来调节通道的活性,从而改变K 的吸收特性。本文综述了高等植物K 吸收运转及调节的分子机制研究方面的最新进展,并对研究的前景进行了展望。     

Modelling and mutational evidence identify the substrate binding site and functional elements in APC amino acid transporters

The Amino acid-Polyamine-Organocation (APC) superfamily is the main family of amino acid transporters found in all domains of life and one of the largest families of secondary transporters. Here, using a sensitive homology threading approach and modelling we show that the predicted structure of APC members is extremely similar to the crystal structures of several prokaryotic transporters belonging to evolutionary distinct protein families with different substrate specificities. All of these proteins, despite having no primary amino acid sequence similarity, share a similar structural core, consisting of two V-shaped domains of five transmembrane domains each, intertwined in an antiparallel topology. Based on this model, we reviewed available data on functional mutations in bacterial, fungal and mammalian APCs and obtained novel mutational data, which provide compelling evidence that the amino acid binding pocket is located in the vicinity of the unwound part of two broken helices, in a nearly identical position to the structures of similar transporters. Our analysis is fully supported by the evolutionary conservation and specific amino acid substitutions in the proposed substrate binding domains. Furthermore, it allows predictions concerning residues that might be crucial in determining the specificity profile of APC members. Finally, we show that two cytoplasmic loops constitute important functional elements in APCs. Our work along with different kinetic and specificity profiles of APC members in easily manipulated bacterial and fungal model systems could form a unique framework for combining genetic, in-silico and structural studies, for understanding the function of one of the most important transporter families.     

Large-scale comparative genomic analyses of cytoplasmic membrane transport systems in prokaryotes

The recent advancements in genome sequencing make it possible for the comparative analyses of essential cellular processes like transport in organisms across the three domains of life. Membrane transporters play crucial roles in fundamental cellular processes and functions in prokaryotic systems. Between 3 and 16% of open reading frames in prokaryotic genomes were predicted to encode membrane transport proteins, emphasizing the importance of transporters in their lifestyles. Hierarchical clustering of phylogenetic profiles of transporter families, which are derived from the presence or absence of a certain transporter family, showed distinct clustering patterns for obligate intracellular organisms, plant/soil-associated microbes and autotrophs. Obligate intracellular organisms possess the fewest types and number of transporters presumably due to their relatively stable living environment, while plant/soil-associated organisms generally encode the largest variety and number of transporters. A group of autotrophs are clustered together largely due to their absence of transporters for carbohydrate and organic nutrients and the presence of transporters for inorganic nutrients. Inside of each group, organisms are further clustered by their phylogenetic properties. These findings strongly suggest the correlation of transporter profiles to both evolutionary history and the overall physiology and lifestyles of the organisms.     

A study of the evolution of inverted-topology repeats from LeuT-fold transporters using AlignMe

X-ray crystal structures have revealed that numerous secondary transporter proteins originally categorized into different sequence families share similar structures, namely, the LeuT fold. The core of this fold consists of two units of five transmembrane helices, whose conformations have been proposed to exchange to form the two alternate states required for transport. That these two units are related implies that LeuT-like transporters evolved from gene-duplication and fusion events. Thus, the origins of this structural repeat may be relevant to the evolution of transport function. However, the lack of significant sequence similarity requires sensitive sequence search methods for analyzing their evolution. To this end, we developed a software application called AlignMe, which can use various types of input information, such as residue hydrophobicity, to perform pairwise alignments of sequences and/or of hydropathy profiles of (membrane) proteins. We used AlignMe to analyze the evolutionary relationships between repeats of the LeuT fold. In addition, we identified proteins from the so-called DedA family that potentially share a common ancestor with these repeats. DedA domains have been implicated in, e.g., selenite uptake; they are found widely distributed across all kingdoms of life; two or more DedA domains are typically found per genome, and some may adopt dual topologies. These results suggest that DedA proteins existed in ancient organisms and may function as dimers, as required for a would-be ancestor of the LeuT fold. In conclusion, we provide novel insights into the evolution of this important structural motif and thus potentially into the alternating-access mechanism of transport itself.