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NTM-host matched infection models for the classification of drug efficacy against rapid and slow growing nontuberculous mycobacteria species
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  • Published: 13 February 2026

NTM-host matched infection models for the classification of drug efficacy against rapid and slow growing nontuberculous mycobacteria species

  • Vincent E. Guglielmi1,
  • Jason E. Cummings1,
  • Nicholas J. Whittel1,
  • Erik A. Langland1 &
  • …
  • Richard A. Slayden1 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Computational biology and bioinformatics
  • Diseases
  • Drug discovery
  • Medical research
  • Microbiology

Abstract

Nontuberculous mycobacteria (NTM) are increasingly recognized as major causes of pulmonary disease worldwide. However, progress in identifying effective clinical treatments is difficult because standardized, high-burden preclinical models that enable rapid quantitative classification and comparison of drug performance in slow-growing mycobacteria (SGM) and rapid-growing mycobacteria (RGM) species are lacking. This study describes a framework for benchmarking treatment efficacy using NTM species-host matched infection models of Mycobacterium avium 2285 in immunocompetent C57BL/6 mice and Mycobacterium abscessus ATCC 19977 in immunodeficient NOD. CB17-Prkdcscid/NCrCrl (NOD-SCID) mice. A consistent high-burden respiratory infection is established by real-time quantification of viable inoculum, ensuring reproducible bacterial lung burden across experiments. The short-course treatment duration provides a rapid and resource-efficient therapeutic window for assessing pharmacological response. Analytical outputs integrate absolute CFU reduction with variance-adjusted effect size (Hedges’ g), categorical efficacy classification, and an MIC-Adjusted Clearance Index to generate potency-normalized measures of efficacy in these models. Performance was validated using a reference panel of antimicrobials representing diverse drug classes and mechanisms of action, including macrolides, rifamycins, fluoroquinolones, and diarylquinolines, to ensure broad benchmarking across pharmacological targets. The framework revealed consistent NTM species-specific patterns of drug performance, with higher potency-adjusted efficacy in M. avium than in M. abscessus, consistent with known clinical behavior. Together, these data establish a reproducible and standardized preclinical platform for early efficacy evaluation, enabling rapid, quantitative benchmarking across standardized RGM and SGM infection models, improving the translational predictability of NTM drug development.

Data availability

Data generated or analyzed during this study are included in this published article. Metadata or related datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ABSL-2:

Animal biosafety level 2

ATCC:

American type culture collection

caMH:

cation-adjusted mueller-hinton broth

7H9/7H11:

Middlebrook growth media for mycobacteria

OADC:

oleic acid–albumin–dextrose–catalase supplement

CFU:

colony forming units

CSU:

Colorado State University

HED:

human-equivalent dose

TPC:

total particle count

ICC:

intact cell count

ICC:TPC ratio:

proportion of intact cells to total particle counts

IACUC:

Institutional animal care and use committee

IND:

Investigational new drug

MACI:

MIC-adjusted clearance index

MIC:

minimum inhibitory concentration

Mtb:

Mycobacterium tuberculosis

NTM:

non-tuberculous mycobacteria

NOD-SCID:

NOD.CB17-Prkdc^scid/NCrCrl mice

OLAW:

Office of laboratory animal welfare

PCA:

principal component analysis

PK/PD:

pharmacokinetics/pharmacodynamics

Q1:

quartile 1 (25th percentile)

Q3:

quartile 3 (75th percentile)

RGM:

rapidly growing mycobacteria

SD:

standard deviation

SGM:

slow growing mycobacteria

SAR:

structure–activity relationship(s)

AZI:

azithromycin

BDQ:

bedaquiline

CLA:

clarithromycin

OFL:

ofloxacin

RFB:

rifabutin

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Acknowledgements

We thank Lab Animal Resources (Colorado State University) for the outstanding care of the animals used in these studies.

Funding

This research received no external funding from a federal agency.

Author information

Authors and Affiliations

  1. Mycobacterial Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, 80525, USA

    Vincent E. Guglielmi, Jason E. Cummings, Nicholas J. Whittel, Erik A. Langland & Richard A. Slayden

Authors
  1. Vincent E. Guglielmi
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  2. Jason E. Cummings
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Contributions

RAS obtained funds for this research and managed the study. RAS and JEC developed the project design. JEC, EAL, NW, and VG performed animal experimentation. JEC, VG, and RAS performed formal data curation. RAS wrote the original draft, and JEC, VG, NW and RAS edited the draft versions.

Corresponding author

Correspondence to Richard A. Slayden.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

All vertebrate animal use at Colorado State University was conducted in accordance with the Guide for the Care and Use of Laboratory Animals, 8th edition (National Academies Press, 2011), and approved by the Colorado State University Institutional Animal Care and Use Committee under protocol number 5172. The university is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC), and maintains an animal welfare assurance number A3572-01, which is on file with the NIH Office of Laboratory Animal Welfare (OLAW). Animals were housed in a state-of-the-art ABSL2 and ABSL3 facilities under the supervision of full-time staff veterinarians and support personnel. Veterinary care was provided in accordance with the American Veterinary Medical Association (AVMA) Guidelines.

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Guglielmi, V.E., Cummings, J.E., Whittel, N.J. et al. NTM-host matched infection models for the classification of drug efficacy against rapid and slow growing nontuberculous mycobacteria species. Sci Rep (2026). https://doi.org/10.1038/s41598-026-40034-3

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  • Received: 05 November 2025

  • Accepted: 10 February 2026

  • Published: 13 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-40034-3

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Keywords

  • Non-tuberculous mycobacteria (NTM)
  • Dual murine infection model
  • Drug efficacy classification
  • Structure-activity relationships (SAR)
  • MIC-adjusted clearance index
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