Peer review process
Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.
Read more about eLife’s peer review process.Editors
- Reviewing EditorBavesh KanaUniversity of the Witwatersrand, Johannesburg, South Africa
- Senior EditorBavesh KanaUniversity of the Witwatersrand, Johannesburg, South Africa
Reviewer #1 (Public review):
A summary of what the authors were trying to achieve:
(1) Identify probiotic candidates based on the phylogenetic proximity and their presence in the lower respiratory tract based on phylogenetic analysis and on meta-analysis of 16S rRNA sequencing of mouse lung samples.
(2) Predefine probiotic candidates with overlapping and competing metabolic profiles based on a simple and easy-to-applicable score, taking carbon source use into consideration.
(3) Confirm the functionality of these candidate probiotics in vitro and define their mechanism of action (niche exclusion by either metabolic competition or active antibacterial strategies).
(4) Confirm the probiotic action in vivo.
Strengths:
The authors attempt to go the whole 9 yards from rational choice of phylogenetic close lower respiratory tract probiotics, over in silico modelling of niche index based on use of similar carbon sources with in vitro confirmation, to in vivo competition experiments in mice.
Weaknesses:
(1) The use of a carbon source is defined as growth to OD600 two SD above the blank level. While allowing a clear cutoff, this procedure does not take into account larger differences in the preferences of carbon sources between the pathogen and the probiotic candidate. If the pathogen is much better at taking up and processing a carbon source, the competition by the probiotic might be biologically irrelevant.
(2) The authors do not take into account the growth of candidate probiotics in the presence of Bt. In monoculture, three of the four most potent candidate probiotics grow to comparable levels as Bt in LSM.
(3) Niche exclusion in vivo is not shown. Mortality of hosts after infection with Bt is not a measure for competition of CP with the pathogen. Only Bt titers would prove a competitive effect. For CP17, less than half of the mice were actually colonized, but still, there is 100% protection. Activation of the host immune system would explain this and has to be excluded as an alternative reason for improved host survival.
Appraisal:
(1) Based on phylogenetic comparison and published resources on lower respiratory tract colonizing bacteria, the authors find a reasonably good number of candidate probiotics that grow in LSM and successfully compete with the pathogenic target bacterium Bt in vitro.
(2) In vivo, only host survival was tested, and a direct competition of CP with Bt by testing for Bt titers was not shown.
Impact:
Niche exclusion based on competition for environmentally provided metabolites is not a new concept and was experimentally tested, e.g. in the intestine. The authors show here that this concept could be translated into the resource-poor environment of the respiratory tract. It remains to be tested if the LSM growth-based competition data in vitro can be translated into niche exclusion in vivo.
Reviewer #2 (Public review):
Summary:
This study aims to establish a rational framework for designing bacterial probiotics against respiratory infections. The central hypothesis is that in vitro antagonism, particularly through metabolic niche overlap with a pathogen, predicts in vivo efficacy.
Strengths:
(1) Systematic pipeline: The study integrates bacterial isolation, in vitro characterization, model development, and in vivo validation into a cohesive workflow.
(2) Quantitative model: The introduction of the Niche Index (NI) and Niche Index Fraction (NIF) provides a novel, quantitative tool for predicting probiotic efficacy based on ecological principles.
(3) Mechanistic insight: The work dissects different modes of action, clearly demonstrating that inhibition can be driven by specialized metabolite production (CP8) or carbon resource competition (e.g., CP7), with lactate utilization identified as a key factor.
Weaknesses:
(1) Limited model generalizability: The predictive power of the NI model is not universal. It fails to account for the in vivo inefficacy of CP8 (a metabolite-dependent inhibitor) and cannot explain the short-term protection conferred by some non-inhibitory CPs in vivo, suggesting unmodeled mechanisms like immune priming are at play.
(2) Preliminary nature of key findings: The emphasis on lactate consumption as a critical predictor, while interesting, is not sufficiently explored to establish its general importance beyond the specific strains and conditions tested.
Appraisal:
The authors successfully achieve their aim of establishing a rational probiotic-design pipeline. The data robustly support the conclusion that metabolic niche overlap predicts efficacy for many strains, while also clearly delineating the model's limitations, as acknowledged by the authors.
Impact:
This work provides a valuable methodological framework for hypothesis-driven probiotic discovery. The quantitative Niche Index offers immediate utility to the field and, with further refinement, has the potential to become a fundamental tool for developing respiratory therapeutics.