Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2024 May 10;10(5):1483-1519.
doi: 10.1021/acsinfecdis.4c00115. Epub 2024 May 1.

Navigating Antibacterial Frontiers: A Panoramic Exploration of Antibacterial Landscapes, Resistance Mechanisms, and Emerging Therapeutic Strategies

Affiliations
Review

Navigating Antibacterial Frontiers: A Panoramic Exploration of Antibacterial Landscapes, Resistance Mechanisms, and Emerging Therapeutic Strategies

Krittika Ralhan et al. ACS Infect Dis. .

Abstract

The development of effective antibacterial solutions has become paramount in maintaining global health in this era of increasing bacterial threats and rampant antibiotic resistance. Traditional antibiotics have played a significant role in combating bacterial infections throughout history. However, the emergence of novel resistant strains necessitates constant innovation in antibacterial research. We have analyzed the data on antibacterials from the CAS Content Collection, the largest human-curated collection of published scientific knowledge, which has proven valuable for quantitative analysis of global scientific knowledge. Our analysis focuses on mining the CAS Content Collection data for recent publications (since 2012). This article aims to explore the intricate landscape of antibacterial research while reviewing the advancement from traditional antibiotics to novel and emerging antibacterial strategies. By delving into the resistance mechanisms, this paper highlights the need to find alternate strategies to address the growing concern.

Keywords: antibacterial; antibiotics; antimicrobial resistance; bacterial infection; multidrug resistance.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Illustration demonstrating action mechanisms of commonly used antibiotics (left side) and resistance mechanisms used by bacteria (right side) to evade the action of antibiotics (individual icons for creating illustration are sourced from www.biorender.com).
Figure 2
Figure 2
Trend landscape map representing the number of documents (journal and patent publications) from 2012 onward for data retrieved from the CAS Content Collection associated with emerging antibacterial strategies (including emerging forms and newer methodologies used in developing antibacterials).
Figure 3
Figure 3
Number of journal and patent publications per year mentioning the use of emerging strategies in antibacterial research over the past decade (2012–2022).
Figure 4
Figure 4
(A) Number of journal and patent publications per year in the field of antibacterial research (shown as blue and yellow bars, respectively) over the past decade (2012–2022). (B) Top countries/regions for the numbers of antibacterial-related journal articles (blue bars) and patents (yellow bars) over the past decade (2012–2022).
Figure 5
Figure 5
(A) Top research institutions in terms of average citation numbers per journal publication between 2012 and 2022. The colors of the bars represent the institution’s country/region: red (China), blue (USA), indigo (Canada), green (Australia), light blue (Singapore), brown (Portugal), orange (India), light green (Republic of Korea), and gray (Israel); the yellow line represents the average number of citations per publication. Top scientific journals with respect to (B) the number of antibacterial research-related articles published and (C) the number of citations they received for the period 2012–2022.
Figure 6
Figure 6
(A) Number of patent publications per year between 2012 and 2022 by commercial (blue) and noncommercial (black) assignees. Top 20 (B) commercial assignees and (C) noncommercial assignees with respect to the number of antibacterial research-related patents published from 2012 to 2022.
Figure 7
Figure 7
Distribution by country of patent publications for commercial assignees (left panel) and noncommercial assignees (right panel). The colors of the bars represent the organization’s country/region: yellow (China), blue (USA), light blue (Republic of Korea), orange (India), magenta (Japan), gray (United Kingdom), and pink (Israel).
Figure 8
Figure 8
Patent flow of antibacterial-related patent filings from different assignee countries/regions to various patent filing offices (center) and final destination patent office (right). The abbreviations in the center and right indicate the patent offices. Standard two- and three-letter codes are used to denote country names corresponding to their patent offices.
Figure 9
Figure 9
Heat map tables indicating number of publications mentioning the top (A) bacterial species, (B) diseases/conditions caused by bacteria, and (C) antibiotic classes used in the field of antibacterials.
Figure 10
Figure 10
Heat map of the relationship between the most used classes of antibiotics (top) and prevalent bacterial species (left) in the field of antibacterials. Data comprises journal and patent publications obtained from the CAS Content Collection for the period 2012 to 2022. Relative frequencies of each bacterial species have been calculated within each class of antibiotics.
Figure 11
Figure 11
Growth in substances associated with antibacterials over 2012–2022 from the CAS Content Collection. Only substances indexed with a therapeutic (THU) or pharmacological activity (PAC) role were included for the analysis.
Figure 12
Figure 12
Distribution of substances associated with antibiotics over 2012–2022 from the CAS Content Collection. Only substances indexed with a therapeutic (THU) or pharmacological activity (PAC) role were included in the analysis. Heat map tables list the top 10 substances co-occurring in those specific classes.
Figure 13
Figure 13
Number of substances of different classes associated with journal publications of antibiotics over 2012–2022 from the CAS Content Collection. Only substances indexed with a therapeutic (THU) or pharmacological activity (PAC) role were included for the analysis. Inset graph shows a zoomed in view with an emphasis on polymers, elements, and alloys to better reflect growth over the past decade.
Figure 14
Figure 14
Sankey graphs indicating co-occurrences between different classes of substances and various bacterial genera in (A) journal and (B) patent publications from the CAS Content Collection for the period 2012–2022. Only substances indexed with a therapeutic (THU) or pharmacological activity (PAC) role were included in the analysis.
Figure 15
Figure 15
Growth in substances for bacterial strains recognized as (A) CDC’s urgent AMR threat, (B) CDC’s serious AMR threat (C) CDC’s AMR watchlist, and (D) ESKAPEE pathogens from the CAS Content Collection for the period 2012–2022. Only substances indexed with a therapeutic (THU) or pharmacological activity (PAC) role were included in the analysis.
Figure 16
Figure 16
Commercial interest in antibiotics (data from PitchBook). (A) Capital invested and deals related to antibiotics for the past decade (2012 to 2022). (B) Geographical distribution of capital invested in 2022 and 2023 in the field of antibiotics. (C) Leading countries or regions in terms of capital invested over 2020–2023. (D) Growth in capital invested over time for a few key countries or regions. Standard three-letter codes are used to represent countries or regions. (E) Distribution of capital invested across different industry types over the past decade.
Figure 17
Figure 17
VOSviewer graph indicating networks of top 150 co-occurring concepts related to the use of AI in the field of antibacterials in the past decade.

Similar articles

Cited by

References

    1. World Health Organization . Antimicrobial resistance. 2021. https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance (accessed November 11, 2023).
    1. Murray C. J. L.; Ikuta K. S.; Sharara F.; Swetschinski L.; Robles Aguilar G.; Gray A.; Han C.; Bisignano C.; Rao P.; Wool E.; Johnson S. C.; Browne A. J.; Chipeta M. G.; Fell F.; Hackett S.; Haines-Woodhouse G.; Kashef Hamadani B. H.; Kumaran E. A. P.; McManigal B.; Achalapong S.; Agarwal R.; Akech S.; Albertson S.; Amuasi J.; Andrews J.; Aravkin A.; Ashley E.; Babin F.-X.; Bailey F.; Baker S.; Basnyat B.; Bekker A.; Bender R.; Berkley J. A.; Bethou A.; Bielicki J.; Boonkasidecha S.; Bukosia J.; Carvalheiro C.; Castañeda-Orjuela C.; Chansamouth V.; Chaurasia S.; Chiurchiù S.; Chowdhury F.; Clotaire Donatien R.; Cook A. J.; Cooper B.; Cressey T. R.; Criollo-Mora E.; Cunningham M.; Darboe S.; Day N. P. J.; De Luca M.; Dokova K.; Dramowski A.; Dunachie S. J.; Duong Bich T.; Eckmanns T.; Eibach D.; Emami A.; Feasey N.; Fisher-Pearson N.; Forrest K.; Garcia C.; Garrett D.; Gastmeier P.; Giref A. Z.; Greer R. C.; Gupta V.; Haller S.; Haselbeck A.; Hay S. I.; Holm M.; Hopkins S.; Hsia Y.; Iregbu K. C.; Jacobs J.; Jarovsky D.; Javanmardi F.; Jenney A. W. J.; Khorana M.; Khusuwan S.; Kissoon N.; Kobeissi E.; Kostyanev T.; Krapp F.; Krumkamp R.; Kumar A.; Kyu H. H.; Lim C.; Lim K.; Limmathurotsakul D.; Loftus M. J.; Lunn M.; Ma J.; Manoharan A.; Marks F.; May J.; Mayxay M.; Mturi N.; Munera-Huertas T.; Musicha P.; Musila L. A.; Mussi-Pinhata M. M.; Naidu R. N.; Nakamura T.; Nanavati R.; Nangia S.; Newton P.; Ngoun C.; Novotney A.; Nwakanma D.; Obiero C. W.; Ochoa T. J.; Olivas-Martinez A.; Olliaro P.; Ooko E.; Ortiz-Brizuela E.; Ounchanum P.; Pak G. D.; Paredes J. L.; Peleg A. Y.; Perrone C.; Phe T.; Phommasone K.; Plakkal N.; Ponce-de-Leon A.; Raad M.; Ramdin T.; Rattanavong S.; Riddell A.; Roberts T.; Robotham J. V.; Roca A.; Rosenthal V. D.; Rudd K. E.; Russell N.; Sader H. S.; Saengchan W.; Schnall J.; Scott J. A. G.; Seekaew S.; Sharland M.; Shivamallappa M.; Sifuentes-Osornio J.; Simpson A. J.; Steenkeste N.; Stewardson A. J.; Stoeva T.; Tasak N.; Thaiprakong A.; Thwaites G.; Tigoi C.; Turner C.; Turner P.; van Doorn H. R.; Velaphi S.; Vongpradith A.; Vongsouvath M.; Vu H.; Walsh T.; Walson J. L.; Waner S.; Wangrangsimakul T.; Wannapinij P.; Wozniak T.; Young Sharma T. E. M. W.; Yu K. C.; Zheng P.; Sartorius B.; Lopez A. D.; Stergachis A.; Moore C.; Dolecek C.; Naghavi M. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 2022, 399 (10325), 629–655. 10.1016/S0140-6736(21)02724-0. - DOI - PMC - PubMed
    1. Santajit S.; Indrawattana N. Mechanisms of Antimicrobial Resistance in ESKAPE Pathogens. BioMed Res. Int. 2016, 2016, 2475067.10.1155/2016/2475067. - DOI - PMC - PubMed
    1. Weiner L. M.; Webb A. K.; Limbago B.; Dudeck M. A.; Patel J.; Kallen A. J.; Edwards J. R.; Sievert D. M. Antimicrobial-Resistant Pathogens Associated With Healthcare-Associated Infections: Summary of Data Reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2011–2014. Infect. Control Hosp. Epidemiol. 2016, 37 (11), 1288–1301. 10.1017/ice.2016.174. - DOI - PMC - PubMed
    1. Weiner-Lastinger L. M.; Abner S.; Edwards J. R.; Kallen A. J.; Karlsson M.; Magill S. S.; Pollock D.; See I.; Soe M. M.; Walters M. S.; Dudeck M. A. Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015–2017. Infect. Control Hosp. Epidemiol. 2020, 41 (1), 1–18. 10.1017/ice.2019.296. - DOI - PMC - PubMed

Publication types

MeSH terms

Substances