MétaCan
Menu
Back to cohort
Record W2064999985 · doi:10.1086/652417

The α‐Enolase of<i>Streptococcus suis</i>: A Previously Well‐Known and Well‐Characterized Protein

2010· letter· en· W2064999985 on OpenAlexaff
Marcelo Gottschalk, J. Daniel Dubreuil, Miriam Esgleas, Josée Harel, Mariela Segura

Bibliographic record

VenueThe Journal of Infectious Diseases · 2010
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Structural Characterization
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEnolaseBiologyComputational biologyImmunologyImmunohistochemistry

Abstract

fetched live from OpenAlex

To the Editor-We read with interest the article by Feng et al [1] that describes the a-enolase of Streptococcus suis (SsEno). S. suis is an important swine pathogen and is considered an emerging zoonotic agent, mainly in Asian countries, and severe human outbreaks with clinical manifestations of streptococcal toxic shock-like syndrome have been reported [2]. As correctly mentioned by the authors, the strain responsible for this episode presents some atypical features, such as a pathogenicity island of 89 kb [3]. Also, in collaboration with the Center for Disease Control in Beijing, we performed multilocus sequence typing and showed that this strain belongs to a different sequence type (ST) that was classified as ST7 [4]. Besides the unique 89-kb pathogenicity island, other putative virulence factors were proposed to explain the higher virulence of this strain [5]. However, more studies are needed to achieve a definitive conclusion. This letter raises concerns about the novelty of results presented by Feng et al [1] and the hypothetical association of SsEno with the highly virulent Chinese S. suisstrain. Three previous articles, specifically on SsEno, were published before the reception date of the manuscript by Feng et al [1]: Esgleas et al (2008) [6], Esgleas et al (2009) [7], and Zhang et al (2009) [8]. Although 2 of these publications were cited [6, 8] by Feng et al [1], in our opinion the authors failed to unambiguously explain previous findings. We would like to complete the information discussed by Feng et al [1], by taking into consideration previously published data. In the abstract of Feng et al [1], it is indicated that “ multiple strategies were used to investigate a new surface protein that has the potential to be a protective antigen.” It was further indicated by the authors that “ these strategies included molecular cloning, biochemical and biophysical analyses, enzymatic assay, immunological approaches (eg, immunoelectron microscopy), and experimental infections of animals.” In fact, the title of the article mentions that SsEno is a protective antigen displayed on the bacterial cell surface. We would like to also take into consideration the following facts. Publication by Esgleas et al (2008) [6]. These authors had previously cloned SsEno, expressed it as a His-tagged fusion protein, and purified it. Similarities with other bacterial enolases were also discussed. The authors demonstrated the biochemical enolase activity of the purified protein. It was shown that SsEno was present in S. suissupernatant, cell wall, and cytoplasmic fraction. Even more, these authors demonstrated that SsEno is expressed on the cell surface, by means of electron microscopy. Unfortunately, in the study of Feng et al [1] these results were partially confirmed by indirect methods, because electron microscopy results were presented as “ preliminary” and not shown. Esgleas et al [6] also clearly demonstrated the role of SsEno on adhesion and invasion of host cells. Publication by Zhang et al (2009) [8]. Similar to Feng et al [1], Zhang et al [8] had previously demonstrated protection with SsEno in a mouse model, by using a method almost identical to that reported by Feng et al [1], including animals of the same age, the same adjuvant, and booster vaccination after 14 days. Similar to Feng et al [1], Zhang et al [8] had previously used immunofluorescence to verify the attachment of SsEno to Hep-2 cells, the same cell line used by Feng et al [1], and had previously reported inhibition of S. suis adherence to Hep-2 cells by SsEno. Publication by Esgleas et al (2009) [7]. Similar to what was reported by Feng et al [1], Esgleas et al (2009) [7] had previously used a very similar enzyme-linked immunosorbent assay and demonstrated that serum from convalescent pigs (different from control pigs) strongly recognize SsEno. Unfortunately, reference to this previous work was not included in the article by Feng et al [1]. It would be extremely hazardous to speculate that “ the presence of [SsEno] on the cell surface could be correlated with high invasiveness of Chinese [S. suis type 2] strains” [1]. In fact, as shown by Esgleas et al [6], all reference strains from the 35 serotypes of S. suis expressed SsEno. In addition, all S. suis type 2 strains tested so far express SsEno at the bacterial surface. SsEno is by far not restricted to the Chinese strain. We believe that Feng et al [1] made a premature and rather incorrect statement regarding the importance of SsEno for the ST7 strain. In conclusion, the information indicating that SsEno is a surface-exposed important antigen that may elicit protection against S. suis infection is not new, and most data had already been published by other research groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.203
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2010
Admission routes1
Has abstractno

Explore more

Same venueThe Journal of Infectious DiseasesSame topicBiochemical and Structural CharacterizationFrench-language works237,207