Evidence map›Paper›PMID 27896376›Full record

ArticleMicrobial ecology2017

Reducing the Bottleneck in Discovery of Novel Antibiotics.

Marcus B Jones, William C Nierman, Yue Shan, Bryan C Frank, Amy Spoering, Losee Ling, Aaron Peoples, Ashley Zullo, Kim Lewis, Karen E Nelson

Abstract read
PubMed Publisher
In one paragraph

Article in Microbial ecology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Perturbation-specific transcriptional mapping for unbiased target elucidation of antibiotics.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Antibacterial Discovery: 21st Century Challenges.Antibiotics (Basel, Switzerland) · 2020
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Role of GntR Family Regulatory GeneBioMed research international · 2017
    Article
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

10 authors.

Marcus B JonesGenomic Medicine, J. Craig Venter Institute, La Jolla, CA, USA. marcusjones06@gmail.com.
William C NiermanGenomic Medicine, J. Craig Venter Institute, La Jolla, CA, USA.
Yue ShanAntimicrobial Discovery Center, Department of Biology, Northeastern University, Boston, MA, USA.
Bryan C FrankGenomic Medicine, J. Craig Venter Institute, La Jolla, CA, USA.
Amy SpoeringNovoBiotic Pharmaceuticals, Cambridge, MA, USA.
Losee LingNovoBiotic Pharmaceuticals, Cambridge, MA, USA.
Aaron PeoplesNovoBiotic Pharmaceuticals, Cambridge, MA, USA.
Ashley ZulloNovoBiotic Pharmaceuticals, Cambridge, MA, USA.
Kim LewisAntimicrobial Discovery Center, Department of Biology, Northeastern University, Boston, MA, USA.
Karen E NelsonGenomic Medicine, J. Craig Venter Institute, La Jolla, CA, USA.

Funding

Uncultured bacteria for the discovery of novel antimicrobialsP01AI118687 · NIAID · NORTHEASTERN UNIVERSITY · PI LEWIS, KIM · 2016 to 2020
$8.9M
NIAID NIH HHS P01 AI118687
6 · The paper itself

Abstract

Most antibiotics were discovered by screening soil actinomycetes, but the efficiency of the discovery platform collapsed in the 1960s. By now, more than 3000 antibiotics have been described and most of the current discovery effort is focused on the rediscovery of known compounds, making the approach impractical. The last marketed broad-spectrum antibiotics discovered were daptomycin, linezolid, and fidaxomicin. The current state of the art in the development of new anti-infectives is a non-existent pipeline in the absence of a discovery platform. This is particularly troubling given the emergence of pan-resistant pathogens. The current practice in dealing with the problem of the background of known compounds is to use chemical dereplication of extracts to assess the relative novelty of a compound it contains. Dereplication typically requires scale-up, extraction, and often fractionation before an accurate mass and structure can be produced by MS analysis in combination with 2D NMR. Here, we describe a transcriptome analysis approach using RNA sequencing (RNASeq) to identify promising novel antimicrobial compounds from microbial extracts. Our pipeline permits identification of antimicrobial compounds that produce distinct transcription profiles using unfractionated cell extracts. This efficient pipeline will eliminate the requirement for purification and structure determination of compounds from extracts and will facilitate high-throughput screen of cell extracts for identification of novel compounds.

Indexed as

Anti-Bacterial AgentsBiological TransportDrug DiscoveryDrug Resistance, Multiple, BacterialGene Expression ProfilingMicrobial Sensitivity TestsSequence Analysis, RNAStaphylococcus aureusStreptomycesAnti-Bacterial AgentsAntibioticsStaphylococcus aureusStreptomycesTranscriptome-based dereplication

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.