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Solute carrier (SLC) proteins represent the largest superfamily of transmembrane transporters. While many of them play key biological roles, their systematic analysis has been hampered by their functional and structural heterogeneity. Based on available nomenclature systems, we hypothesized that many as yet unidentified SLC transporters exist in the human genome, which await further systematic analysis. Here, we present criteria for defining “SLC-likeness” to curate a set of “SLC-like” protein families from the Transporter Classification Database (TCDB) and Protein families (Pfam) databases. Computational sequence similarity searches surprisingly identified ∼120 more proteins in human with potential SLC-like properties compared to previous annotations. Interestingly, several of these have documented transport activity in the scientific literature. To complete the overview of the “SLC-ome”, we present an algorithm to classify SLC-like proteins into protein families, investigating their known functions and evolutionary relationships to similar proteins from 6 other clinically relevant experimental organisms, and pinpoint structural orphans. We envision that our work will serve as a stepping stone for future studies of the biological function and the identification of the natural substrates of the many under-explored SLC transporters, as well as for the development of new therapeutic applications, including strategies for personalized medicine and drug delivery.

Upon discovery of the first archaeal species in the 1970s, life has been subdivided into three domains: Eukarya, Archaea, and Bacteria. However, the organization of the three-domain tree of life has been challenged following the discovery of archaeal lineages such as the TACK and Asgard superphyla. The Asgard Superphylum has emerged as the closest archaeal ancestor to eukaryotes, potentially improving our understanding of the evolution of life forms. We characterized the transportomes and their substrates within four metagenome-assembled genomes (MAGs), that is, Odin-, Thor-, Heimdall- and Loki-archaeota as well as the fully sequenced genome ofCandidatusPrometheoarchaeum syntrophicum strain MK-D1 that belongs to the Loki phylum. Using the Transporter Classification Database (TCDB) as reference, candidate transporters encoded within the proteomes were identified based on sequence similarity, alignment coverage, compatibility of hydropathy profiles, TMS topologies and shared domains. Identified transport systems were compared within the Asgard superphylum as well as within dissimilar eukaryotic, archaeal and bacterial organisms. From these analyses, we infer that Asgard organisms rely mostly on the transport of substrates driven by the proton motive force (pmf), the proton electrochemical gradient which then can be used for ATP production and to drive the activities of secondary carriers. The results indicate that Asgard archaea depend heavily on the uptake of organic molecules such as lipid precursors, amino acids and their derivatives, and sugars and their derivatives. Overall, the majority of the transporters identified are more similar to prokaryotic transporters than eukaryotic systems although several instances of the reverse were documented. Taken together, the results support the previous suggestions that the Asgard superphylum includes organisms that are largely mixotrophic and anaerobic but more clearly define their metabolic potential while providing evidence regarding their relatedness to eukaryotes.

The Transporter Classification Database (TCDB; tcdb.org) is a freely accessible reference resource, which provides functional, structural, mechanistic, medical and biotechnological information about transporters from organisms of all types. TCDB is the only transport protein classification database adopted by the International Union of Biochemistry and Molecular Biology (IUBMB) and now (October 1, 2020) consists of 20 653 proteins classified in 15 528 non-redundant transport systems with 1567 tabulated 3D structures, 18 336 reference citations describing 1536 transporter families, of which 26% are members of 82 recognized superfamilies. Overall, this is an increase of over 50% since the last published update of the database in 2016. This comprehensive update of the database contents and features include (i) adoption of a chemical ontology for substrates of transporters, (ii) inclusion of new superfamilies, (iii) a domain-based characterization of transporter families for the identification of new members as well as functional and evolutionary relationships between families, (iv) development of novel software to facilitate curation and use of the database, (v) addition of new subclasses of transport systems including 11 novel types of channels and 3 types of group translocators and (vi) the inclusion of many man-made (artificial) transmembrane pores/channels and carriers.

The Major Facilitator Superfamily (MFS) is currently the largest characterized superfamily of transmembrane secondary transport proteins. Its diverse members are found in essentially all organisms in the biosphere and function by uniport, symport, and/or antiport mechanisms. In 1993 we first named and described the MFS which then consisted of 5 previously known families that had not been known to be related, and by 2012 we had identified a total of 74 families, classified phylogenetically within the MFS, all of which included only transport proteins. This superfamily has since expanded to 89 families, all included under TC# 2.A.1, and a few transporter families outside of TC# 2.A.1 were identified as members of the MFS. In this study, we assign nine previously unclassified protein families in the Transporter Classification Database (TCDB; http://www.tcdb.org) to the MFS based on multiple criteria and bioinformatic methodologies. In addition, we find integral membrane domains distantly related to partial or full-length MFS permeases in Lysyl tRNA Synthases (TC# 9.B.111), Lysylphosphatidyl Glycerol Synthases (TC# 4.H.1), and cytochrome b(561) transmembrane electron carriers (TC# 5.B.2). Sequence alignments, overlap of hydropathy plots, compatibility of repeat units, similarity of complexity profiles of transmembrane segments, shared protein domains and 3D structural similarities between transport proteins were analyzed to assist in inferring homology. The MFS now includes 105 families.

Outbreaks of gummy stem blight (GSB), an emerging seed pumpkin disease, have increased in number and have become more widespread in recent years. Previously we reported that Stagonosporopsis cucurbitacearum (Sc.) is the dominant fungal cause of pumpkin seedling GSB in Northeast China, where it has greatly reduced crop yields in that region. Here, high-throughput whole-genome sequencing and assembly of the Sc. genome were conducted toward revealing pathogenic molecular regulatory mechanisms involved in fungal growth and development. Zq-1 as representative Sc. strain, DNA of Zq-1was prepared for genomic sequencing, we obtained 5.24 Gb of high-quality genomic sequence data via PacBio RS II sequencing. After sequence data was processed to filter out low quality reads, a hierarchical genome-assembly process was employed that generated a genome sequence of 35.28 Mb in size. A total of 9844 genes were predicted, including 237 non-coding RNAs, 1024 genes encoding proteins with signal peptides, 2066 transmembrane proteins and 756 secretory proteins.Transcriptional identification revealed 54 differentially expressed secretory proteins. Concurrently, 605, 130 and 2869 proteins were matched in the proprietary databases Carbohydrate-Active EnZymes database (CAZyme), Transporter Classification Database (TCDB) and Pathogen–Host Interactions database (PHI), respectively. And 96 and 36 DEGs were identified form PHI database and CAZyme database, respectively. In addition, contig00011.93 was an up-regulated DEG involving ATP-binding cassette metabolism in the procession of infection. In order to test relevance of gene predictions to GSB, DEGs with potential pathogenic relevance were revealed through transcriptome data analysis of Sc. strains pre- and post-infection of pumpkin. Interestingly, Sc. and Leptosphaeria maculans (Lm.) exhibited relatively similar with genome lengths, numbers of protein-coding genes and other characteristics. This work provides a foundation for future exploration of additional Sc. gene functions toward the development of more effective GSB control strategies.

Prebiotics are increasingly used as food supplements, especially in infant formulas, to modify the functioning and composition of the microbiota. However, little is currently known about the mechanisms of prebiotic recognition and transport by gut bacteria, while these steps are crucial in their metabolism. In this study, we established a new strategy to profile the specificity of oligosaccharide transporters, combining microbiomics, genetic locus and strain engineering, and state-of-the art metabolomics. We revisited the transporter classification database and proposed a new way to classify these membrane proteins based on their structural and mechanistic similarities. Based on these developments, we identified and characterized, at the molecular level, a fructooligosaccharide transporting phosphotransferase system, which constitutes a biomarker of diet and gut pathology. The deciphering of this prebiotic metabolization mechanism by a nonbeneficial bacterium highlights the controversial use of prebiotics, especially in the context of chronic gut diseases., Prebiotic oligosaccharides, such as fructooligosaccharides, are increasingly being used to modulate the composition and activity of the gut microbiota. However, carbohydrate utilization analyses and metagenomic studies recently revealed the ability of deleterious and uncultured human gut bacterial species to metabolize these functional foods. Moreover, because of the difficulties of functionally profiling transmembrane proteins, only a few prebiotic transporters have been biochemically characterized to date, while carbohydrate binding and transport are the first and thus crucial steps in their metabolization. Here, we describe the molecular mechanism of a phosphotransferase system, highlighted as a dietary and pathology biomarker in the human gut microbiome. This transporter is encoded by a metagenomic locus that is highly conserved in several human gut Firmicutes, including Dorea species. We developed a generic strategy to deeply analyze, in vitro and in cellulo, the specificity and functionality of recombinant transporters in Escherichia coli, combining carbohydrate utilization locus and host genome engineering and quantification of the binding, transport, and growth rates with analysis of phosphorylated carbohydrates by mass spectrometry. We demonstrated that the Dorea fructooligosaccharide transporter is specific for kestose, whether for binding, transport, or phosphorylation. This constitutes the biochemical proof of effective phosphorylation of glycosides with a degree of polymerization of more than 2, extending the known functional diversity of phosphotransferase systems. Based on these new findings, we revisited the classification of these carbohydrate transporters. IMPORTANCE Prebiotics are increasingly used as food supplements, especially in infant formulas, to modify the functioning and composition of the microbiota. However, little is currently known about the mechanisms of prebiotic recognition and transport by gut bacteria, while these steps are crucial in their metabolism. In this study, we established a new strategy to profile the specificity of oligosaccharide transporters, combining microbiomics, genetic locus and strain engineering, and state-of-the art metabolomics. We revisited the transporter classification database and proposed a new way to classify these membrane proteins based on their structural and mechanistic similarities. Based on these developments, we identified and characterized, at the molecular level, a fructooligosaccharide transporting phosphotransferase system, which constitutes a biomarker of diet and gut pathology. The deciphering of this prebiotic metabolization mechanism by a nonbeneficial bacterium highlights the controversial use of prebiotics, especially in the context of chronic gut diseases.

Background The electric organ of Tetronarce californica (an electric ray formerly known as Torpedo californica) is a classic preparation for biochemical studies of cholinergic neurotransmission. To broaden the usefulness of this preparation, we have performed a transcriptome assembly of the presynaptic component of the electric organ (the electric lobe). We combined our assembled transcriptome with a previous transcriptome of the postsynaptic electric organ, to define a MetaProteome containing pre- and post-synaptic components of the electric organ. Results Sequencing yielded 102 million paired-end 100 bp reads. De novo Trinity assembly was performed at Kmer 25 (default) and Kmers 27, 29, and 31. Trinity, generated around 103,000 transcripts, and 78,000 genes per assembly. Assemblies were evaluated based on the number of bases/transcripts assembled, RSEM-EVAL scores and informational content and completeness. We found that different assemblies scored differently according to the evaluation criteria used, and that while each individual assembly contained unique information, much of the assembly information was shared by all assemblies. To generate the presynaptic transcriptome (electric lobe), while capturing all information, assemblies were first clustered and then combined with postsynaptic transcripts (electric organ) downloaded from NCBI. The completness of the resulting clustered predicted MetaProteome was rigorously evaluated by comparing its information against the predicted proteomes from Homo sapiens, Callorhinchus milli, and the Transporter Classification Database (TCDB). Conclusions In summary, we obtained a MetaProteome containing 92%, 88.5%, and 66% of the expected set of ultra-conserved sequences (i.e., BUSCOs), expected to be found for Eukaryotes, Metazoa, and Vertebrata, respectively. We cross-annotated the conserved set of proteins shared between the T. californica MetaProteome and the proteomes of H. sapiens and C. milli, using the H. sapiens genome as a reference. This information was used to predict the position in human pathways of the conserved members of the T. californica MetaProteome. We found proteins not detected before in T. californica, corresponding to processes involved in synaptic vesicle biology. Finally, we identified 42 transporter proteins in TCDB that were detected by the T. californica MetaProteome (electric fish) and not selected by a control proteome consisting of the combined proteomes of 12 widely diverse non-electric fishes by Reverse-Blast-Hit Blast. Combined, the information provided here is not only a unique tool for the study of cholinergic neurotransmission, but it is also a starting point for understanding the evolution of early vertebrates. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3890-4) contains supplementary material, which is available to authorized users.

Transport systems comprise roughly 10% of all proteins in a cell, playing critical roles in many processes. Improving and expanding their classification is an important goal that can affect studies ranging from comparative genomics to potential drug target searches. It is not surprising that different classification systems for transport proteins have arisen, be it within a specialized database, focused on this functional class of proteins, or as part of a broader classification system for all proteins. Two such databases are the Transporter Classification Database (TCDB) and the Protein family (Pfam) database. As part of a long-term endeavor to improve consistency between the two classification systems, we have compared transporter annotations in the two databases to understand the rationale for differences and to improve both systems. Differences sometimes reflect the fact that one database has a particular transporter family while the other does not. Differing family definitions and hierarchical organizations were reconciled, resulting in recognition of 69 Pfam 'Domains of Unknown Function', which proved to be transport protein families to be renamed using TCDB annotations. Of over 400 potential new Pfam families identified from TCDB, 10% have already been added to Pfam, and TCDB has created 60 new entries based on Pfam data. This work, for the first time, reveals the benefits of comprehensive database comparisons and explains the differences between Pfam and TCDB. The Author 2015. Published by Oxford University Press.

Background: Bilirubin is a highly-hydrophobic tetrapyrrole which binds to plasma albumin. It is conjugated in the liver to glucuronic acid, and the water-soluble glucuronides are excreted in urine and bile. The membrane transporters of bilirubin diglucuronide are well-known. Still undefined are however the transporters performing the uptake of bilirubin from the blood into the liver, a process known to be fast and not rate-limited. The biological importance of this process may be appraised by considering that in normal adults 200–300 mg of bilirubin are produced daily, as a result of the physiologic turnover of hemoglobin and cellular cytochromes. Nevertheless, research in this field has yielded controversial and contradicting results. We have undertaken a systematic review of the literature, believing in its utility to improve the existing knowledge and promote further advancements. Methods: We have sourced the PubMed database until 30 June 2017 by applying 5 sequential searches. Screening and eligibility criteria were applied to retain research articles reporting results obtained by using bilirubin molecules in membrane transport assays in vitro or by assessing serum bilirubin levels in in vivo experiments. Results: We have identified 311 articles, retaining 44, reporting data on experimental models having 6 incremental increases of complexity (isolated proteins, membrane vesicles, cells, organ fragments, in vivo rodents, and human studies), demonstrating the function of 19 membrane transporters, encoded by either SLCO or ABC genes. Three other bilirubin transporters have no gene, though one, i.e., bilitranslocase, is annotated in the Transporter Classification Database. Conclusions: This is the first review that has systematically examined the membrane transporters for bilirubin and its conjugates. Paradoxically, the remarkable advancements in the field of membrane transport of bilirubin have pointed to the elusive mechanism(s) enabling bilirubin to diffuse into the liver as if no cellular boundary existed.

Bdellovibrio, δ-proteobacteria, including B. bacteriovorus (Bba) and B. exovorus (Bex), are obligate predators of other Gram-negative bacteria. While Bba grows in the periplasm of the prey cell, Bex grows externally. We have analyzed and compared the transport proteins of these 2 organisms based on the current contents of the Transporter Classification Database (TCDB; www.tcdb.org). Bba has 103 transporters more than Bex, 50% more secondary carriers, and 3 times as many MFS carriers. Bba has far more metabolite transporters than Bex as expected from its larger genome, but there are 2 times more carbohydrate uptake and drug efflux systems, and 3 times more lipid transporters. Bba also has polyamine and carboxylate transporters lacking in Bex. Bba has more than twice as many members of the Mot-Exb family of energizers, but both may have energizers for gliding motility. They use entirely different types of systems for iron acquisition. Both contain unexpectedly large numbers of pseudogenes and incomplete systems, suggesting that they are undergoing genome size reduction. Interestingly, all 5 outer-membrane receptors in Bba are lacking in Bex. The 2 organisms have similar numbers and types of peptide and amino acid uptake systems as well as protein and carbohydrate secretion systems. The differences observed correlate with and may account, in part, for the different lifestyles of these 2 bacterial predators.

The amino acid-polyamine-organoCation (APC) superfamily is the second largest superfamily of secondary carriers currently known. In this study, we establish homology between previously recognized APC superfamily members and proteins of seven new families. These families include the PAAP (Putative Amino Acid Permease), LIVCS (Branched Chain Amino Acid:Cation Symporter), NRAMP (Natural Resistance-Associated Macrophage Protein), CstA (Carbon starvation A protein), KUP (K⁺ Uptake Permease), BenE (Benzoate:H⁺ Virginia Symporter), and AE (Anion Exchanger). The topology of the well-characterized human Anion Exchanger 1 (AE1) conforms to a UraA-like topology of 14 TMSs (12 α-helical TMSs and 2 mixed coil/helical TMSs). All functionally characterized members of the APC superfamily use cation symport for substrate accumulation except for some members of the AE family which frequently use anion:anion exchange. We show how the different topologies fit into the framework of the common LeuT-like fold, defined earlier (Proteins. 2014 Feb;82(2):336-46), and determine that some of the new members contain previously undocumented topological variations. All new entries contain the two 5 or 7 TMS APC superfamily repeat units, sometimes with extra TMSs at the ends, the variations being greatest within the CstA family. New, functionally characterized members transport amino acids, peptides, and inorganic anions or cations. Except for anions, these are typical substrates of established APC superfamily members. Active site TMSs are rich in glycyl residues in variable but conserved constellations. This work expands the APC superfamily and our understanding of its topological variations.

Currently, there are more than 800 well characterized human membrane transport proteins (including channels and transporters) and there are estimates that about 10% (approx. 2000) of all human genes are related to transport. Membrane transport proteins are of interest as potential drug targets, for drug delivery, and as a cause of side effects and drug–drug interactions. In light of the development of Open PHACTS, which provides an open pharmacological space, we analyzed selected membrane transport protein classification schemes (Transporter Classification Database, ChEMBL, IUPHAR/BPS Guide to Pharmacology, and Gene Ontology) for their ability to serve as a basis for pharmacology driven protein classification. A comparison of these membrane transport protein classification schemes by using a set of clinically relevant transporters as use-case reveals the strengths and weaknesses of the different taxonomy approaches.

We evaluated topological predictions for nine different programs, HMMTOP, TMHMM, SVMTOP, DAS, SOSUI, TOPCONS, PHOBIUS, MEMSAT-SVM (hereinafter referred to as MEMSAT), and SPOCTOPUS. These programs were first evaluated using four large topologically well-defined families of secondary transporters, and the three best programs were further evaluated using topologically more diverse families of channels and carriers. In the initial studies, the order of accuracy was: SPOCTOPUS > MEMSAT > HMMTOP > TOPCONS > PHOBIUS > TMHMM > SVMTOP > DAS > SOSUI. Some families, such as the Sugar Porter Family (2.A.1.1) of the Major Facilitator Superfamily (MFS; TC #2.A.1) and the Amino Acid/Polyamine/Organocation (APC) Family (TC #2.A.3), were correctly predicted with high accuracy while others, such as the Mitochondrial Carrier (MC) (TC #2.A.29) and the K+ transporter (Trk) families (TC #2.A.38), were predicted with much lower accuracy. For small, topologically homogeneous families, SPOCTOPUS and MEMSAT were generally most reliable, while with large, more diverse superfamilies, HMMTOP often proved to have the greatest prediction accuracy. We next developed a novel program, TM-STATS, that tabulates HMMTOP, SPOCTOPUS or MEMSAT-based topological predictions for any subdivision (class, subclass, superfamily, family, subfamily, or any combination of these) of the Transporter Classification Database (TCDB; www.tcdb.org) and examined the following subclasses: α-type channel proteins (TC subclasses 1.A and 1.E), secreted pore-forming toxins (TC subclass 1.C) and secondary carriers (subclass 2.A). Histograms were generated for each of these subclasses, and the results were analyzed according to subclass, family and protein. The results provide an update of topological predictions for integral membrane transport proteins as well as guides for the development of more reliable topological prediction programs, taking family-specific characteristics into account.

The Transporter Classification Database (TCDB), freely accessible at http://www.tcdb.org, is a relational database containing sequence, structural, functional and evolutionary information about transport systems from a variety of living organisms, based on the International Union of Biochemistry and Molecular Biology-approved transporter classification (TC) system. It is a curated repository for factual information compiled largely from published references. It uses a functional/phylogenetic system of classification, and currently encompasses about 5000 representative transporters and putative transporters in more than 500 families. We here describe novel software designed to support and extend the usefulness of TCDB. Our recent efforts render it more user friendly, incorporate machine learning to input novel data in a semiautomatic fashion, and allow analyses that are more accurate and less time consuming. The availability of these tools has resulted in recognition of distant phylogenetic relationships and tremendous expansion of the information available to TCDB users.

We have designed a freely accessible program, PhyST, which allows the automated characterization of any family of homologous proteins within the Transporter Classification Database. The program performs an NCBI-PSI-BLAST search and reports (1) the average protein sequence length with standard deviations, (2) the average predicted number of transmembrane segments, (3) the total number of homologues retrieved, (4) a quantitative list of all source phyla, and (5) potential fusion proteins of sizes considerably exceeding the average size of the proteins retrieved. We have applied this program to 58 families of holins, and the results are presented. The results show that holins are very rarely fused to other protein domains, suggesting that holins form transmembrane pores as homooligomers without the participation of other proteins or protein domains.

The Bio-V Suite is a collection of Python scripts designed specifically for bioinformatic research regarding transport protein evolution. The Bio-V Suite contains nine powerful programs for Unix-based environments, each of which can be run as a standalone tool or be accessed in a programmatic manner. These programs and their functions are as follows. The transmembrane alpha-helical statistical prediction tool (TMStats) generates topological statistics for transport proteins. The Global Sequence Alignment Tool (GSAT) performs shuffle-based binary alignments and is fully scalable. It can cross-compare two FASTA files or individual sequences. Protocol1 performs remote PSI-Blast searches and filters redundant/similar sequences and annotates them. Protocol2 finds homologues between FASTA lists and generates graphical reports. The Targeted Smith-Waterman Search (TSSearch) uses a rapid search algorithm to find distant homologues in FASTA files in a heuristic manner. SSearch is the exhaustive version of TSSearch. Genome-Blast (GBlast) will identify potential transport proteins in any genome/proteome file or find similar transport protein homologues between two different genomes/proteomes before generating a graphical report. AncientRep (AR) will find putative transmembrane repeat units using a list of homologues. DefineFamily (DF) will generate a FASTA list to represent an entire Transporter Classification family. These nine programs are tabulated with descriptions of their capabilities in Table 1. [Table: see text].

Plant secretory trichomes have a unique capacity for chemical synthesis and secretion and have been described as biofactories for the production of natural products. However, until recently, most trichome-specific metabolic pathways and genes involved in various trichome developmental stages have remained unknown. Furthermore, only a very limited amount of plant trichome genomics information is available in scattered databases. We present an integrated “omics” database, TrichOME, to facilitate the study of plant trichomes. The database hosts a large volume of functional omics data, including expressed sequence tag/unigene sequences, microarray hybridizations from both trichome and control tissues, mass spectrometry-based trichome metabolite profiles, and trichome-related genes curated from published literature. The expressed sequence tag/unigene sequences have been annotated based upon sequence similarity with popular databases (e.g. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Transporter Classification Database). The unigenes, metabolites, curated genes, and probe sets have been mapped against each other to enable comparative analysis. The database also integrates bioinformatics tools with a focus on the mining of trichome-specific genes in unigenes and microarray-based gene expression profiles. TrichOME is a valuable and unique resource for plant trichome research, since the genes and metabolites expressed in trichomes are often underrepresented in regular non-tissue-targeted cDNA libraries. TrichOME is freely available at http://www.planttrichome.org/.

© 2014 The Author(s) Journal of Eukaryotic Microbiology © 2014 International Society of Protistologists. Integral membrane transport proteins homologous to those found in the Transporter Classification Database (TCDB; www.tcdb.org) were identified and bioinformatically characterized by transporter class, family, and substrate specificity in three ciliates, Paramecium tetraurelia (Para), Tetrahymena thermophila (Tetra), and Ichthyophthirius multifiliis (Ich). In these three organisms, 1,326 of 39,600 proteins (3.4%), 1,017 of 24,800 proteins (4.2%), and 504 out of 8,100 proteins (6.2%) integral membrane transport proteins were identified, respectively. Thus, an inverse relationship was observed between the % transporters identified and the number of total proteins per genome reported. This surprising observation provides insight into the evolutionary process, giving rise to genome reduction following whole genome duplication (as in the case of Para) or during pathogenic association with a host organism (Ich). Of these transport proteins in Para and Tetra, about 41% were channels (more than any other type of organism studied), 31% were secondary carriers (fewer than most eukaryotes) and 26% were primary active transporters, mostly ATP-hydrolysis driven (more than most other eukaryotes). In Ich, the number of channels was selectively reduced by 66%, relative to Para and Tetra. Para has four times more inorganic anion transporters than Tetra, and Ich has nonselectively lost most of these. Tetra and Ich preferentially transport sugars and monocarboxylates while Para prefers di- and tricarboxylates. These observations serve to characterize the transport proteins of these related ciliates, providing insight into their nutrition and metabolism.

Protein phylogeny, based on primary amino acid sequence relatedness, reflects the evolutionary process and therefore provides a guide to structure, mechanism and function. Any two proteins that are related by common descent are expected to exhibit similar structures and functions to a degree proportional to the degree of their sequence similarity; but two independently evolving proteins should not. This principle provides the impetus to define protein phylogenetic relationships and interrelate families when possible. In this mini-review, we summarize the computational approaches and criteria we use to establish common evolutionary origin. We apply these tools to define distant superfamily relationships between several previously recognized transport protein families. In some cases, available structural and functional data are evaluated in order to substantiate our claim that molecular phylogeny provides a reliable guide to protein structure and function.

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.

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.

The Transporter Classification Database (TCDB; http://www.tcdb.org) serves as a common reference point for transport protein research. The database contains more than 10 000 non-redundant proteins that represent all currently recognized families of transmembrane molecular transport systems. Proteins in TCDB are organized in a five level hierarchical system, where the first two levels are the class and subclass, the second two are the family and subfamily, and the last one is the transport system. Superfamilies that contain multiple families are included as hyperlinks to the five tier TC hierarchy. TCDB includes proteins from all types of living organisms and is the only transporter classification system that is both universal and recognized by the International Union of Biochemistry and Molecular Biology. It has been expanded by manual curation, contains extensive text descriptions providing structural, functional, mechanistic and evolutionary information, is supported by unique software and is interconnected to many other relevant databases. TCDB is of increasing usefulness to the international scientific community and can serve as a model for the expansion of database technologies. This manuscript describes an update of the database descriptions previously featured in NAR database issues. © 2013 The Author(s). Published by Oxford University Press.

Holins are small “hole-forming” transmembrane proteins that mediate bacterial cell lysis during programmed cell death or following phage infection. We have identified fifty two families of established or putative holins and have included representative members of these proteins in the Transporter Classification Database (TCDB; www.tcdb.org). We have identified the organismal sources of members of these families, calculated their average protein sizes, estimated their topologies and determined their relative family sizes. Topological analyses suggest that these proteins can have 1, 2, 3 or 4 transmembrane α-helical segments (TMSs), and members of a single family are frequently, but not always, of a single topology. In one case, proteins of a family proved to have either 2 or 4 TMSs, and the latter arose by intragenic duplication of a primordial 2 TMS protein-encoding gene resembling the former. Using established statistical approaches, some of these families have been shown to be related by common descent. Seven superfamilies, including 21 of the 52 recognized families were identified. Conserved motif and Pfam analyses confirmed most superfamily assignments. These results serve to expand upon the scope of channel-forming bacterial holins.

Rhodopirellula baltica (R. baltica) is a Planctomycete, known to have intracellular membranes. Because of its unusual cell structure and ecological significance, we have conducted comprehensive analyses of its transmembrane transport proteins. The complete proteome of R. baltica was screened against the Transporter Classification Database (TCDB) to identify recognizable integral membrane transport proteins. 342 proteins were identified with a high degree of confidence, and these fell into several different classes. R. baltica encodes in its genome channels (12%), secondary carriers (33%), and primary active transport proteins (41%) in addition to classes represented in smaller numbers. Relative to most non-marine bacteria, R. baltica possesses a larger number of sodium-dependent symporters but fewer proton-dependent symporters, and it has dimethylsulfoxide (DMSO) and trimethyl-amine-oxide (TMAO) reductases, consistent with its Na(+)-rich marine environment. R. baltica also possesses a Na(+)-translocating NADH:quinone dehydrogenase (Na(+)-NDH), a Na(+) efflux decarboxylase, two Na(+)-exporting ABC pumps, two Na(+)-translocating F-type ATPases, two Na(+):H(+) antiporters and two K(+):H(+) antiporters. Flagellar motility probably depends on the sodium electrochemical gradient. Surprisingly, R. baltica also has a complete set of H(+)-translocating electron transport complexes similar to those present in α-proteobacteria and eukaryotic mitochondria. The transport proteins identified proved to be typical of the bacterial domain with little or no indication of the presence of eukaryotic-type transporters. However, novel functionally uncharacterized multispanning membrane proteins were identified, some of which are found only in Rhodopirellula species, but others of which are widely distributed in bacteria. The analyses lead to predictions regarding the physiology, ecology and evolution of R. baltica.

Transport proteins function in the translocation of ions, solutes and macromolecules across cellular and organellar membranes. These integral membrane proteins fall into >600 families as tabulated in the Transporter Classification Database (www.tcdb.org). Recent studies, some of which are reported here, define distant phylogenetic relationships between families with the creation of superfamilies. Several of these are analyzed using a novel set of programs designed to allow reliable prediction of phylogenetic trees when sequence divergence is too great to allow the use of multiple alignments. These new programs, called SuperfamilyTree1 and 2 (SFT1 and 2), allow display of protein and family relationships, respectively, based on thousands of comparative BLAST scores rather than multiple alignments. Superfamilies analyzed include: (1) Aerolysins, (2) RTX Toxins, (3) Defensins, (4) Ion Transporters, (5) Bile/Arsenite/Riboflavin Transporters, (6) Cation:Proton Antiporters, and (7) the Glucose/Fructose/Lactose superfamily within the prokaryotic phosphoenol pyruvate-dependent Phosphotransferase System. In addition to defining the phylogenetic relationships of the proteins and families within these seven superfamilies, evidence is provided showing that the SFT programs outperform programs that are based on multiple alignments whenever sequence divergence of superfamily members is extensive. The SFT programs should be applicable to virtually any superfamily of proteins or nucleic acids.

Background Ichthyophthirius multifiliis, commonly known as Ich, is a highly pathogenic ciliate responsible for 'white spot', a disease causing significant economic losses to the global aquaculture industry. Options for disease control are extremely limited, and Ich's obligate parasitic lifestyle makes experimental studies challenging. Unlike most well-studied protozoan parasites, Ich belongs to a phylum composed primarily of free-living members. Indeed, it is closely related to the model organism Tetrahymena thermophila. Genomic studies represent a promising strategy to reduce the impact of this disease and to understand the evolutionary transition to parasitism. Results We report the sequencing, assembly and annotation of the Ich macronuclear genome. Compared with its free-living relative T. thermophila, the Ich genome is reduced approximately two-fold in length and gene density and three-fold in gene content. We analyzed in detail several gene classes with diverse functions in behavior, cellular function and host immunogenicity, including protein kinases, membrane transporters, proteases, surface antigens and cytoskeletal components and regulators. We also mapped by orthology Ich's metabolic pathways in comparison with other ciliates and a potential host organism, the zebrafish Danio rerio. Conclusions Knowledge of the complete protein-coding and metabolic potential of Ich opens avenues for rational testing of therapeutic drugs that target functions essential to this parasite but not to its fish hosts. Also, a catalog of surface protein-encoding genes will facilitate development of more effective vaccines. The potential to use T. thermophila as a surrogate model offers promise toward controlling 'white spot' disease and understanding the adaptation to a parasitic lifestyle.

BackgroundMembrane transporters play crucial roles in living cells. Experimental characterization of transporters is costly and time-consuming. Current computational methods for transporter characterization still require extensive curation efforts, especially for eukaryotic organisms. We developed a novel genome-scale transporter prediction and characterization system called TransportTP that combined homology-based and machine learning methods in a two-phase classification approach. First, traditional homology methods were employed to predict novel transporters based on sequence similarity to known classified proteins in the Transporter Classification Database (TCDB). Second, machine learning methods were used to integrate a variety of features to refine the initial predictions. A set of rules based on transporter features was developed by machine learning using well-curated proteomes as guides.ResultsIn a cross-validation using the yeast proteome for training and the proteomes of ten other organisms for testing, TransportTP achieved an equivalent recall and precision of 81.8%, based on TransportDB, a manually annotated transporter database. In an independent test using the Arabidopsis proteome for training and four recently sequenced plant proteomes for testing, it achieved a recall of 74.6% and a precision of 73.4%, according to our manual curation.ConclusionsTransportTP is the most effective tool for eukaryotic transporter characterization up to date.

The ATP-binding cassette (ABC) superfamily consists of both importers and exporters. These transporters have, by tradition, been classified according to the ATP hydrolyzing constituents, which are monophyletic. The evolutionary origins of the transmembrane porter proteins/domains are not known. Using five distinct computer programs, we here provide convincing statistical data suggesting that the transmembrane domains of ABC exporters are polyphyletic, having arisen at least three times independently. ABC1 porters arose by intragenic triplication of a primordial two-transmembrane segment (TMS)-encoding genetic element, yielding six TMS proteins. ABC2 porters arose by intragenic duplication of a dissimilar primordial three-TMS-encoding genetic element, yielding a distinctive protein family, nonhomologous to the ABC1 proteins. ABC3 porters arose by duplication of a primordial four-TMS-encoding genetic element, yielding either eight- or 10-TMS proteins. We assign each of 48 of the 50 currently recognized families of ABC exporters to one of the three evolutionarily distinct ABC types. Currently available high-resolution structural data for ABC porters are fully consistent with our findings. These results provide guides for future structural and mechanistic studies of these important transport systems.

Motivation: Membrane transport proteins play a crucial role in the import and export of ions, small molecules or macromolecules across biological membranes. Currently, there are a limited number of published computational tools which enable the systematic discovery and categorization of transporters prior to costly experimental validation. To approach this problem, we utilized a nearest neighbor method which seamlessly integrates homologous search and topological analysis into a machine-learning framework. Results: Our approach satisfactorily distinguished 484 transporter families in the Transporter Classification Database, a curated and representative database for transporters. A five-fold cross-validation on the database achieved a positive classification rate of 72.3% on average. Furthermore, this method successfully detected transporters in seven model and four non-model organisms, ranging from archaean to mammalian species. A preliminary literature-based validation has cross-validated 65.8% of our predictions on the 11 organisms, including 55.9% of our predictions overlapping with 83.6% of the predicted transporters in TransportDB. Availability and Supplementary information: http://bioinfo.noble.org/manuscript-support/transporter/ Contact: pzhao@noble.org

The Transporter Classification Database (TCDB) is a web accessible, curated, relational database containing sequence, classification, structural, functional and evolutionary information about transport systems from a variety of living organisms. TCDB is a curated repository for factual information compiled from >10,000 references, encompassing approximately 3000 representative transporters and putative transporters, classified into >400 families. The transporter classification (TC) system is an International Union of Biochemistry and Molecular Biology approved system of nomenclature for transport protein classification. TCDB is freely accessible at http://www.tcdb.org. The web interface provides several different methods for accessing the data, including step-by-step access to hierarchical classification, direct search by sequence or TC number and full-text searching. The functional ontology that underlies the database structure facilitates powerful query searches that yield valuable data in a quick and easy way. The TCDB website also offers several tools specifically designed for analyzing the unique characteristics of transport proteins. TCDB not only provides curated information and a tool for classifying newly identified membrane proteins, but also serves as a genome transporter-annotation tool.

We here describe the transporter classification (TC) system that provides a rational means of classifying all transmembrane transport systems found in living organisms. The availability of this system provides a framework for the use of bioinformatic technologies to answer fundamental questions about the functions, mechanisms, and evolutionary pathways taken for the appearance of these systems. Such advances are discussed.

SUMMARY 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.

Three-dimensional structures have been elucidated for very few integral membrane proteins. Computer methods can be used as guides for estimation of solute transport protein structure, function, biogenesis, and evolution. In this paper the application of currently available computer programs to over a dozen distinct families of transport proteins is reviewed. The reliability of sequence-based topological and localization analyses and the importance of sequence and residue conservation to structure and function are evaluated. Evidence concerning the nature and frequency of occurrence of domain shuffling, splicing, fusion, deletion, and duplication during evolution of specific transport protein families is also evaluated. Channel proteins are proposed to be functionally related to carriers. It is argued that energy coupling to transport was a late occurrence, superimposed on preexisting mechanisms of solute facilitation. It is shown that several transport protein families have evolved independently of each other, employing different routes, at different times in evolutionary history, to give topologically similar transmembrane protein complexes. The possible significance of this apparent topological convergence is discussed.

Bdellovibrio bacteriovorus is a bacterial parasite with an unusual lifestyle. It grows and reproduces in the periplasm of a host prey bacterium. The complete genome sequence of B. bacteriovorus has recently been reported. We have reanalyzed the transport proteins encoded within the B. bacteriovorus genome according to the current content of the Transporter Classification Database. A comprehensive analysis is given on the types and numbers of transport systems that B. bacteriovorus has. In this regard, the potential protein secretory capabilities of at least four types of inner-membrane secretion systems and five types of outer-membrane secretion systems are described. Surprisingly, B. bacteriovorus has a disproportionate percentage of cytoplasmic membrane channels and outer-membrane porins. It has far more TonB/ExbBD-type systems and MotAB-type systems for energizing outer-membrane transport and motility than does Escherichia coli. Analysis of probable substrate specificities of its transporters provides clues to its metabolic preferences. Interesting examples of gene fusions and of potentially overlapping genes are also noted. Our analyses provide a comprehensive, detailed appreciation of the transport capabilities of B. bacteriovorus. They should serve as a guide for functional experimental analyses.

Integral membrane proteins fulfil important roles in many crucial biological processes, including cell signalling, molecular transport and bioenergetic processes. Advancements in experimental techniques are revealing high resolution structures for an increasing number of membrane proteins. Yet, these structures are rarely resolved in complex with membrane lipids. In 2015, the MemProtMD pipeline was developed to allow the automated lipid bilayer assembly around new membrane protein structures, released from the Protein Data Bank (PDB). To make these data available to the scientific community, a web database (http://memprotmd.bioch.ox.ac.uk) has been developed. Simulations and the results of subsequent analysis can be viewed using a web browser, including interactive 3D visualizations of the assembled bilayer and 2D visualizations of lipid contact data and membrane protein topology. In addition, ensemble analyses are performed to detail conserved lipid interaction information across proteins, families and for the entire database of 3506 PDB entries. Proteins may be searched using keywords, PDB or Uniprot identifier, or browsed using classification systems, such as Pfam, Gene Ontology annotation, mpstruc or the Transporter Classification Database. All files required to run further molecular simulations of proteins in the database are provided.