Evidence map›Paper›PMID 21086128›Full record

ArticleCurrent microbiology2011

In vivo studies of Clostridium perfringens in mouse gas gangrene model.

Nabonita Sengupta, Syed Imteyaz Alam

Abstract read
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In one paragraph

Article in Current microbiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Proteomic tools to decipher microbial community structure and functioning.Environmental science and pollution research international · 2015
    Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nabonita SenguptaBiotechnology Division, Defence Research & Development Establishment, Gwalior, 474002, India. nabonita.s@gmail.com
Syed Imteyaz Alam

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the pathogenesis of infectious diseases requires comprehensive knowledge of the proteins expressed by the pathogen during in vivo growth in the host. Proteomics provides the tools for such analyses but the protocols required to purify sufficient quantities of the pathogen from the host organism are currently lacking. In this study, we have separated Clostridium perfringens, a highly virulent bacterium and potential BTW agent, from the peritoneal fluid of infected mice using Percoll density gradient centrifugation. The bacterium could be isolated in quantities sufficient to carry out meaningful proteomic comparisons with in vitro grown bacteria. Furthermore, the isolates were found to be virtually free from contaminating host proteins. Microscopy revealed major morphological changes under host conditions at different stages of infection. Profile of immunogenic proteins from in vivo- and TPYG-grown whole cell lysate using mouse anti-gangrene serum indicated over-expression of several proteins especially in the low molecular weight region. Expression of two virulence determinants, ornithine carbamoyl transferase (cOTC), and cystathionine beta-lyase (CBL), under in vivo conditions has also been studied. Two-dimensional gel analysis revealed a host induced proteome which was apparently different in comparison to in vitro grown cells. Detailed proteomic elucidation of differentially expressed proteins shown here is likely to provide valuable insight towards understanding the complexity of the adaptive response of C. perfringens to the host environment.

Indexed as

Disease Models, AnimalAnimalsBacterial ProteinsCentrifugation, Density GradientClostridium perfringensFemaleGas GangreneMiceMice, Inbred BALB CProteomeBacterial ProteinsProteome

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.