Beware of Moving Targets: Reference Proteome Content Fluctuates Substantially Over the Years

Sirota, Fernanda L.; Batagov, Arsen O.; Schneider, Georg; Eisenhaber, Birgit; Eisenhaber, Frank; Maurer‐Stroh, Sebastian

doi:10.1142/s0219720012500205

Cited by 12 publications

(11 citation statements)

References 45 publications

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“…We are aware that proteome datasets are “moving targets” that have dramatically changed over the years and probably will continue to do so to some extent in the future [83]. Yet, we think that currently available protein sequence sets are sufficiently good for our purposes, as we search for statistical properties in the TMH context only.…”

Section: Methodsmentioning

confidence: 99%

Charged residues next to transmembrane regions revisited: “Positive-inside rule” is complemented by the “negative inside depletion/outside enrichment rule”

et al. 2017

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BackgroundTransmembrane helices (TMHs) frequently occur amongst protein architectures as means for proteins to attach to or embed into biological membranes. Physical constraints such as the membrane’s hydrophobicity and electrostatic potential apply uniform requirements to TMHs and their flanking regions; consequently, they are mirrored in their sequence patterns (in addition to TMHs being a span of generally hydrophobic residues) on top of variations enforced by the specific protein’s biological functions.ResultsWith statistics derived from a large body of protein sequences, we demonstrate that, in addition to the positive charge preference at the cytoplasmic inside (positive-inside rule), negatively charged residues preferentially occur or are even enriched at the non-cytoplasmic flank or, at least, they are suppressed at the cytoplasmic flank (negative-not-inside/negative-outside (NNI/NO) rule). As negative residues are generally rare within or near TMHs, the statistical significance is sensitive with regard to details of TMH alignment and residue frequency normalisation and also to dataset size; therefore, this trend was obscured in previous work. We observe variations amongst taxa as well as for organelles along the secretory pathway. The effect is most pronounced for TMHs from single-pass transmembrane (bitopic) proteins compared to those with multiple TMHs (polytopic proteins) and especially for the class of simple TMHs that evolved for the sole role as membrane anchors.ConclusionsThe charged-residue flank bias is only one of the TMH sequence features with a role in the anchorage mechanisms, others apparently being the leucine intra-helix propensity skew towards the cytoplasmic side, tryptophan flanking as well as the cysteine and tyrosine inside preference. These observations will stimulate new prediction methods for TMHs and protein topology from a sequence as well as new engineering designs for artificial membrane proteins.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-017-0404-4) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Charged residues next to transmembrane regions revisited: “Positive-inside rule” is complemented by the “negative inside depletion/outside enrichment rule”

et al. 2017

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“…Overall, our re-annotation resulted in 27878 (out of 27988 reported annotations) Pfam domain hits which span across 17517 sequences over 5719 unique domain models. Since the complete human proteome is a moving scientific target [23], the re-annotated set used here is only for benchmarking purpose only. The list of originally-reported and re-computed domain annotations for the human UniProt/SwissProt sequences is available at the xHMMER3x2 website (see Additional file 2).…”

Section: Resultsmentioning

confidence: 99%

xHMMER3x2: Utilizing HMMER3’s speed and HMMER2’s sensitivity and specificity in the glocal alignment mode for improved large-scale protein domain annotation

Yap

Eisenhaber

et al. 2016

Biol Direct

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BackgroundWhile the local-mode HMMER3 is notable for its massive speed improvement, the slower glocal-mode HMMER2 is more exact for domain annotation by enforcing full domain-to-sequence alignments. Since a unit of domain necessarily implies a unit of function, local-mode HMMER3 alone remains insufficient for precise function annotation tasks. In addition, the incomparable E-values for the same domain model by different HMMER builds create difficulty when checking for domain annotation consistency on a large-scale basis.ResultsIn this work, both the speed of HMMER3 and glocal-mode alignment of HMMER2 are combined within the xHMMER3x2 framework for tackling the large-scale domain annotation task. Briefly, HMMER3 is utilized for initial domain detection so that HMMER2 can subsequently perform the glocal-mode, sequence-to-full-domain alignments for the detected HMMER3 hits. An E-value calibration procedure is required to ensure that the search space by HMMER2 is sufficiently replicated by HMMER3. We find that the latter is straightforwardly possible for ~80% of the models in the Pfam domain library (release 29). However in the case of the remaining ~20% of HMMER3 domain models, the respective HMMER2 counterparts are more sensitive. Thus, HMMER3 searches alone are insufficient to ensure sensitivity and a HMMER2-based search needs to be initiated. When tested on the set of UniProt human sequences, xHMMER3x2 can be configured to be between 7× and 201× faster than HMMER2, but with descending domain detection sensitivity from 99.8 to 95.7% with respect to HMMER2 alone; HMMER3’s sensitivity was 95.7%. At extremes, xHMMER3x2 is either the slow glocal-mode HMMER2 or the fast HMMER3 with glocal-mode. Finally, the E-values to false-positive rates (FPR) mapping by xHMMER3x2 allows E-values of different model builds to be compared, so that any annotation discrepancies in a large-scale annotation exercise can be flagged for further examination by dissectHMMER.ConclusionThe xHMMER3x2 workflow allows large-scale domain annotation speed to be drastically improved over HMMER2 without compromising for domain-detection with regard to sensitivity and sequence-to-domain alignment incompleteness. The xHMMER3x2 code and its webserver (for Pfam release 27, 28 and 29) are freely available at http://xhmmer3x2.bii.a-star.edu.sg/.ReviewersReviewed by Thomas Dandekar, L. Aravind, Oliviero Carugo and Shamil Sunyaev. For the full reviews, please go to the Reviewers’ comments section.Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-016-0163-0) contains supplementary material, which is available to authorized users.

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“…Special attention is needed for the vast arrays of functionally uncharacterized genome sections in human and most other organisms. With regard to protein-coding regions, the annotation status of non-globular segments is especially unsatisfactory [6,[175][176][177][178]. Since many PTMs are harbored in such segments, the research dedicated to elucidate the functional role of PTMs promises to have important impact.…”

Section: Discussionmentioning

confidence: 99%

Single‐residue posttranslational modification sites at the N‐terminus, C‐terminus or in‐between: To be or not to be exposed for enzyme access

et al. 2015

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Many protein posttranslational modifications (PTMs) are the result of an enzymatic reaction. The modifying enzyme has to recognize the substrate protein's sequence motif containing the residue(s) to be modified; thus, the enzyme's catalytic cleft engulfs these residue(s) and the respective sequence environment. This residue accessibility condition principally limits the range where enzymatic PTMs can occur in the protein sequence. Non‐globular, flexible, intrinsically disordered segments or large loops/accessible long side chains should be preferred whereas residues buried in the core of structures should be void of what we call canonical, enzyme‐generated PTMs. We investigate whether PTM sites annotated in UniProtKB (with MOD_RES/LIPID keys) are situated within sequence ranges that can be mapped to known 3D structures. We find that N‐ or C‐termini harbor essentially exclusively canonical PTMs. We also find that the overwhelming majority of all other PTMs are also canonical though, later in the protein's life cycle, the PTM sites can become buried due to complex formation. Among the remaining cases, some can be explained (i) with autocatalysis, (ii) with modification before folding or after temporary unfolding, or (iii) as products of interaction with small, diffusible reactants. Others require further research how these PTMs are mechanistically generated in vivo.

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Beware of Moving Targets: Reference Proteome Content Fluctuates Substantially Over the Years

Cited by 12 publications

References 45 publications

Charged residues next to transmembrane regions revisited: “Positive-inside rule” is complemented by the “negative inside depletion/outside enrichment rule”

Charged residues next to transmembrane regions revisited: “Positive-inside rule” is complemented by the “negative inside depletion/outside enrichment rule”

xHMMER3x2: Utilizing HMMER3’s speed and HMMER2’s sensitivity and specificity in the glocal alignment mode for improved large-scale protein domain annotation

Single‐residue posttranslational modification sites at the N‐terminus, C‐terminus or in‐between: To be or not to be exposed for enzyme access

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