A Decennials Study of the Trend of antibiotics studies in China

doi:10.21203/rs.3.rs-2228640/v1

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A Decennials Study of the Trend of antibiotics studies in China

https://doi.org/10.21203/rs.3.rs-2228640/v1

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published 24 Nov, 2023

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Antibiotics are one of the greatest inventions in human history and are used worldwide on an enormous scale. Besides its extensive usage in medical and veterinary arenas to treat and prevent the infection, its application is very prominent in other fields, including agriculture, aquaculture, and horticulture. In recent decades, the increased consumption of antibiotics in China saw a vast increase in its production and disposal in various environments. However, in this post-antibiotic era, the abuse and misuse of these valuable compounds could lead to the unreversible consequence of drug resistance. In China, antibiotics are given a broad discussion in various fields to reveal their impact on both human/animals health and the environment. To our knowledge, we are the first paper to look back at the development trend of antibiotic-related studies in China with qualitative and quantitative bibliometric analysis from the past decades. Our study identified and analysed 5559 papers from its inception (1991) to December 6, 2021, from the Web of Science Core Collection database. However, with few authors and institutions focusing on long term studies, we found the quality of contributions were uneven. Studies mainly focused on areas such as food science, clinical research, and environmental studies, including Molecular biology, genetics and environmental, ecotoxicology, and nutrition, which indicate possible primary future trends. Our study reports on including potentially new keywords, studies' milestones, and their contribution to antibiotic research. We offer potential topics that may be important in upcoming years that could help guide future research.

Bibliometric

Antibiotics

ARGs

China

Citespace

Antibiotics are one of the most effective pharmaceuticals in human history and are used to treat various infections and diseases caused by microorganisms. The usage of these valuable compounds could stretch back millennia for medicinal applications by scholars in Egypt and China (Hutchings et al., 2019). At the turn of the 20^th century, the first antibiotic mycophenolic acid, was discovered from Penicillium glaucum in 1893 by Bartolomeo Gosio from Italy. In the year 1910, the first man-made antibiotic was witnessed, which was named arsphenamine (Salvarsan), developed by chemist Alfred Bertheim. The antibiotic is still in circulation for its medicinal application in treating syphilis (Nicolaou and Rigol, 2018). In the 1940s, Penicillin was accidentally discovered by Dr. Alexander Fleming; the substance was then purified and saved millions of lives. Since the discovery of Penicillin, we have gone through a golden era of antibiotic discovery, and to this date, there are about 100 reported types of antibiotics that are being synthesized and widely used in different fields (Choudri, 2018).

Antibiotics can be classified in various ways, and the most common classes of categorization is through their chemical and molecular structures, including: β-lactams, Macrolides, Tetracyclines, Quinolones, Aminoglycosides, Sulphonamides, Glycopeptides and Oxazolidinones (Etebu and Arikekpar, 2016). In the past decades, antibiotics have been the pillar of medicine in the treatment and prevention of diseases among communities of human and animals worldwide. In 2010, 70 billion individual doses were administered and consumed worldwide from the top seven antibiotic classes, which roughly equals to about 10 pills per person per year. Also, the data showed an increasing trend in antibiotic consumption in the future (Blaser, 2016). Moreover, small doses of antibiotics are used as grown promoters and proficiency enhancers on food animals to improve the economic gains. Principally used in US and European countries, there is also a rapid increase of anitbiotics in developing countries as well. In 2030, it is estimated that the consumption of antibiotics will rise by 67% (Van et al., 2020).

Unfortunately, this development of antibiotics is accompanied with substantial negative impacts, which has now become one of the biggest threats to global health, food security, and development (WHO, 2021). Misuse of antibiotics could cause various disturbances to the human body, including direct toxicity, allergies, carcinogenic effects, reproductive disorders, and destruction of the gastrointestinal microbiota, especially in children (Oliveira et al., 2020). According to Uzan-Yulzari et al. (2021), the antibiotic-induced gut microbiome perturbation in the neonatal period could induce poor neurodevelopmental outcomes. More importantly, the high load of antibiotics in the environment could promote the selection and spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) (Lyu et al., 2020). One serious outcome is that the clinical implications of new antibiotics could be potentially inhibited by the subsequent protective or resistant mechanisms developed by bacteria to reduce their susceptibility (Hogberg et al., 2010). Besides evolving through mutation, the mobile genetic elements (MGEs) (such as integrons and transposons) carrying ARGs can spread antibiotic resistance through horizontal gene transfer (HGT) within and between species (Zheng et al., 2021). Due to various anthropogenic activities, ARG mobility is inevitable, spreading across borders and becoming an international problem (Li et al., 2021b). A study by Qiao et al. (2018) reported that the colistin-resistance genes mcr-1, initially reported in China, has spread over globe, resulted in several variants (mcr-2 and mcr-3) through mutation, transmission and gene transfer.

China is the largest producer and consumer of antibiotics and utilized around 162,000 tons of antibiotics in 2013, which is over a hundred times compared to the United Kingdom and nine times to the United States (Lyu et al., 2020). In China, nearly half of antibiotics (46%) are used in livestock farms to improve production or prevent infections (Hao, 2015). Livestock waste containing the antibiotics residue is further utilized as fertilizer for crop production and aquaculture (Xiong et al., 2015; Pan and Chu, 2017), leading to their entry into the soil and aquatic ecosystems. Due to the high dissolvability characteristic of antibiotics and the lack of effective treatment measurements, domestic wastewater treatment plants (WWTPs) (Gao et al., 2012), landfills (Wu et al., 2015), hospital and medicine production (Tao et al., 2013) could also release antibiotics directly or indirectly into different environments. Multiple reports have shown that up to 70% of antibiotics are directly or indirectly released into diverse environments in China, including surface water (Liu et al., 2018b), soil (Lyu et al., 2020), sediment (Wu et al., 2016) and groundwater environment (Chen et al., 2018). Therefore, many policies have been implemented by the Chinese government to guide the appropriate antibiotic use in clinical and agricultural settings in recent five years.

In the past 15 years, with the consciousness of the severe condition and impacts of antibiotics in China, many scientific publications investigated and reported the contamination status, relevant impacts, and various treatment methods (Anh et al., 2021). Based on these studies, the conclusion of the current status and the prediction of future trends in antibiotics research are of high demand. As one of the most well-known, and widely used methods, Bibliometric analysis can decipher and map the cumulative scientific knowledge and evolutionary differences in a broad field by quantitively analyzing mass data in rigorous ways (Donthu et al., 2021). By identifying spatial-temporal variations of research topics, research hotspots, and assessment of different tags, including author and keywords, a comprehensive overview of the knowledge and a potential guide for the future could be established (Chen and Song, 2019; Li et al., 2021a). This study performed two categories of bibliometric analysis, including performance analysis and scientific mapping skills like co-words analysis, document co-citation analysis (DCA) and structural variation analysis (SVA). The aims this study were to address three questions: (1) What are the scenarios of publications and hotspots? (2) What are the intellectual bases for antibiotics studies in China? (3) What are the possible future directions of antibiotics research in China?

2.1 Data Collection

Web of Science Core Collection (WoSCC) is one of the most trusted databases with editorial processes to ensure data quality. In this study, the following key terms: "Antibiotics" OR "Antibiotic" OR "ARGs" AND "China" were used to search in the database from the inception (1985) to December 6, 2021. The term antibiotic pollution, antibiotic resistance bacteria, antimicrobial resistance, mobile genetic elements, and antibiotic resistance gene were not included since all these terminologies fall under the category of Antibiotics and ARG. This order confirms that "China" has become a must included term, and the topic should consist of information related to antibiotics. A total of 5559 documents were selected and exported to provide a comprehensive view of the field; the results were not restricted by languages, document types, or publication years. After that, the data were exported in .txt files, including complete records and cited references.

2.2 Analysis and Map Visualization

Performance analysis and science mapping are two significant procedures in bibliometrics. The performance analysis applied in our study aims to evaluate the scientific factors, including countries, institutions, authors, and their impact on the field (Cobo et al., 2011). As a hallmark of bibliometrics study, this could help us show the background of antibiotic studies in China. Besides the productivity per active year of publication (PAY), the top 10 authors, institutions, and journals were analyzed with Microsoft Office 2020 and Oigin9.0 (2019).

Scientific mapping is a general process for domain analysis and visualization conducted with scientometric tools. By highlighting the change in trends, theories, and patterns, scientific mapping could explore and interpret the intellectual structures and dynamic patterns (Chen, 2017). In order to analyze the aims of this study, various scientific mapping skills including co-words analysis, document co-citation analysis (DCA), dual-map overlay, and structural variation analysis (SVA), were used to report a comprehensive analysis on the antibiotic studies in China.

Theoretically, if two words occur in an article simultaneously, it is considered to have a closer relationship than other pairs of words (Zhu et al., 2020). Co-word analysis can explore the interaction between words and examine the trends or evolution of the research theme (Tan Luc et al., 2020). VOSviewer (Leiden University), and Scimago Graphica were applied to visualize the Co-word analysis in this article. Especially, the terms were selected based on 'all keywords', in which the words were retrieved from the title, abstract, and author keywords of articles. Also, the minimum occurrence of terms was set to 50 to ensure that only high-frequency terms are used in networking drawing.

Compared to co-word analysis, document co-cited analysis (DCA) was used to inspect the whole topic—"antibiotics studies in China" in a much more specific way. The concept underlying the methods connects the two earlier literature cited by later literature (Tang and Tsai, 2016). Considering that the number of co-citations could represent the similarity of publications in terms of content, the analysis could draw the inner structures of research disciplines and form clusters of similar ideas, methods, or findings (GMÜR, 2003). Because DCA is the connection between the intellectual base (cited reference) and research front (citing articles), the trails of the intellectual base could reflect the evolution of the research front (Chen, 2006). Scientific research and its development could be mapped as an overall structure of disciplines. The major themes in "antibiotic studies in China" and how these specialties evolve during development were determined. The analysis was presented through the software Citespace based on Java. With 5559 documents imported to the software, the timeline was set from 1991 to 2022; the slice length was set to 1. The top 100 most cited papers for each time slice were selected to build the network. The documents were clustered by LSI algorithms and then named based on key terms extracted from titles, abstracts, and none phrases. Burst detection and timeline view were conducted for the key clusters for further analysis.

In the final part of the article, the conclusion of the historical path was based on a journal perspective, from which the projection of future trends was presented. A dual-map overlay is a new method for portfolio analysis that represents the overall dataset in the context of a global science map generated based on over 10,000 journals with Blondel clustering configuration (Chen and Leydesdorff, 2014). It can characterize the science field on a macroscopic scale and track the historical movement of scientific frontiers from both sources and targets of citations (the trajectory). Citespace was used for visualization, and the trajectory of time was mapped. It should be noted that the documents published in 2022 (a total of ≥23 articles) were excluded to avoid their possible impacts on the overall year trajectory due to the limited number.

With a clear cognition of the past information, the future trend is also predicted with Citespace using SVA. The principal of the analysis is to recognize the possible breakthrough of scientific papers in terms of their degrees in altering the existing intellectual structure (boundary-spanning mechanism) (Chen, 2012). During these processes, the analysis was performed based on a co-citation network, similar to the work of Sebastian and Chen (2021). The top 100 papers were selected, and the publication time frame and sliding window are set to 5 ([Y-5, Y-1]). Thus ensuring that the baseline network calculated can be constructed with papers published five years prior to 2021. The flow chart of the research framework is shown in Fig. S1.

3.1 Background Of Antibiotics Studies In China

The papers were categorized into nine types. Most papers were research articles, followed by reviews (5.78%) and proceedings (1.73%). Based on the retrieved papers, the development of Chinese antibiotic studies was divided into three stages (Fig. S2). From our understanding; started from 1991 with two papers focusing on the positive effects of antibiotics. In this infancy stage, Yang (1991) considered an urgent need to change the antibiotic industry structure, to increase antibiotics productivity and explore new antibiotics in China. At that time, new biotechnological techniques, including gene transformation and protoplast fusion, were implemented to explore new antibiotics. In the same year, Xu (1991) pointed out that antibiotics like Oxalysine could be efficient treatment methods for cancer and hepatitis. After that, there was a four-year gap until 1996.

In 1996, adverse impacts, including hearing impairment (Morioka et al., 1996) and increased antibiotic susceptibilities (Kam, 1996), were observed in China for the first time, except for the (positive) usage of antibiotics in agriculture (Weller, 1996), poultry farming (Sato, 1996) and medication (Wang, 1996). The total publications per year grew slowly, showing that the antibiotic research garnered little attention on its effects and impacts, although several scientists started noticing the severity of the condition. Some actions taken during this period included the establishment of Mohnarin and the Chinese Ministry of Health Centre for antibacterial Surveillance (Mohcas) in 2006. However, Xiao et al. (2013) found that "these strategies are unsuccessful due to the lack of mandatory regulations ".

The number of published papers has increased at a fast speed since 2006. With a rapid-development phase witnessed in the following years and the total annual publications increased from 109 (2010) to 861 (2020), accounting for about 94% of total publications (Fig. S2). The outcome matched the policy status in China; for example, health care reforms were launched in 2009, and a series of policies focused on antibiotics was promulgated, including a national stewardship campaign against the overuse of antibiotics (2011), Circular for Further promotion of the Regulation on Antibiotics (2012) and Action plan for Water Pollution Control (2015) (Mossialos, 2016). These policies stimulated the research on antibiotics in various fields. According to the Web of Science classification, "Microbiology", "Environmental Science and Ecology", "Infectious diseases", "Pharmacology pharmacy" and "Public Environmental Occupational Health" are the top five popular research areas, and the top three areas occupy over 60% of the total documents (Fig. S2), highlighting that antibiotics have been of concern not only in the clinical settings and agriculture but also in the environment in China. It is also worth noting that "others" (Fig. S2) also contributed to antibiotics studies in China, and the trend is constantly growing. We believe “others” refers to multidisciplinary studies that reported, investigated, or discussed antibiotic-related information. Given their increase over the years, we could assume that these kinds of studies will gain more traction in the future. Because we observed a significant positive correlation between year and total annual publications (r = 0.98*), it could be positively anticipated that the number will further increase in the future.

3.1.1 Contribution of Authors

A total of 24685 authors engaged in antibiotics-related research in China, and the top ten authors and co-cited authors were listed in Table 1. Only 300 authors published more than ten papers, which account for 1.2% of the total number. We found 67 authors published over 20 papers which gives a relatively high impact on the field, occupying 0.2% of the total authors. Most authors (76%) contribute one paper, showing that only a few authors constantly focused on antibiotics studies in China. Our analysis indicate that the ten authors with the highest frequency are Zhang Jumei, Wu Qingping, Wang Juan, Wu Shi, Ding Yu, and Chen Moutong, and there is evidence that they have a strong collaboration link between them (Fig. S3). It could be ascribed to: (1) all the authors are located in geographic proximity; in this case, they are all from Guangzhou city, which helps promote their connection (2) the authors come from the same research background, for example, food science, and microbiology. Some of their high-cited papers through collaboration are Prevalence and Characterization of Monophasic Salmonella Serovar 1,4,[5],12:i:- of Food Origin in China (citations = 70), and Characterization and transfer of antibiotic resistance in lactic acid bacteria from fermented food products (Citations = 152) undoubtedly represents their interests in antibiotic resistance and ARGs transfer among bacteria in food (Nawaz et al., 2011; Yang et al., 2015). At the same time, Wang Yang is an expert in veterinary medicine with his paper: Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study cited most among all papers (citations = 2774). This paper reported the first case of plasmid-mediated colistin resistance mechanism, mcr-1, demonstrated that we have lost the last-resort therapies in treating multidrug-resistant Gram-negative bacteria, and its quick spreading from meat to humans would raise a global concern (Liu et al., 2016). Following his research, Yu Yunsong, who ranked sixth among authors, contributed to another critical paper (citations = 137) about the prevalence of mcr-1 in China from bloodstream infections (Quan et al., 2017). Famous in drug-resistance medication, Yu Yunsong also reported ST11, the dominant clone of KPCs (Klebsiella pneumoniae carbapenemase)-produced by Klebsiella pneumoniae (a mechanism of carbapenem resistance) in China (Qi et al., 2011).

An interesting result was observed when we ranked the author by citation; certain authors with fewer papers have higher total citations. For example, although Ying Guangguo had only half the papers of Zhang Jumei (Citations = 1159), his citation (Citations = 4784) was around four times higher. This phenomenon indicates an imbalance between the quality and quantity of papers in antibiotic research in China, indicating the need for an overall improvement. The highly co-cited author can present the influential researchers in the research domains. Two international standards-making organizations (CLSI and WHO) have the highest citations, which proves their high reliability among researchers (Table 1). A comprehensive evaluation of antibiotics emission and fate in the river basins of China: Source analysis, multimedia modelling, and linkage to bacterial resistance by Zhang QQ (Zhang, 2015) and Diverse and abundant antibiotic resistance genes in Chinese swine farms by Zhu YG (Zhu et al., 2013) were cited > 900 times in total (Table 1).

Table 1

The top 10 authors and co-cited authors (n%)
Rank	Author	N (%)	Co-cited author	Citations
1	Zhang Jumei	64 (1.15%)	CLSI*	972
2	Wu Qingping	64 (1.15%)	WHO*	918
3	Wang Juan	49 (0.86%)	Zhang QQ	534
4	Wang Yang	47 (0.86%)	Luo Y	467
5	Wu Shi	40 (0.72%)	Kummer K	450
6	Yu Yunsong	39 (0.68%)	Zhu YG	416
7	Ding Yu	37 (0.66%)	Xu WH	411
8	Chen Moutong	34 (0.63%)	Zhou LJ	406
9	Wang Jun	34 (0.61%)	WANG Y	406
10	Ying Guangguo	32 (0.58%)	Poirel L	342

*CLSI = Clinical and Laboratory Standards Institution

* WHO = World Health Organization

3.2 Contribution of Journals and Institutions

The top 10 citing and cited journals with their characteristics (such as impact factor (IF)) are listed in Table 2. The studies related to antibiotics in China have been published in 1112 journals. However, only 100 journals published more than ten papers, and 48 published more than 20 papers. The result indicates that very few journals constantly draw attention to the issue in China. Journal Frontiers in Microbiology published 218 papers (3.9% of the total) has the highest productivity, followed by Science of the Total Environment (3.8%), Infection and Drug Resistance (2.3%), Environmental Pollution (2.2%), and Environmental Science and Pollution Research (2.2%). Most top citing journals share similar interests with popular research areas, especially microbiology, environmental science, and infectious diseases. Similar to Zhang et al. (2020), we calculated the average citations per paper of a journal (Citation/N) to indicate journals' quality and found that papers with low frequency could have higher citations. Journal of Hazardous Materials and Journal of Antimicrobial Chemotherapy are journals with the highest Citation/N ratio, suggesting that they have an excellent reputation for antibiotic studies in China. This is also evidenced by their high impact factor which helps to prove this standpoint. Compared to citing journals (IF = 5.3), cited journals have a higher average impact factor (IF ≥ 6.9). The high-quality sources of the references indicate that the intellectual base of our study is trustworthy and stable.

Table 2

The top 10 citing journals and cited journals (n%)
Rank	Journals	N (%)	Citations	Citation/N	IF (2020)	Cited Journal	Counts	Co-citation	IF (2020)
1	Frontiers in Microbiology	218 (3.9%)	3441	15.8	5.640	Antimicrobial Agents and Chemotherapy	7874	7874	5.191
2	Science of the Total Environment	209 (3.8%)	8864	42.4	7.963	Science of the Total Environment	6448	5214	7.963
3	Infection and Drug Resistance	128 (2.3%)	504	3.93	4.003	Environmental Science & Technology	6368	3404	9.028
4	Environmental Pollution	122 (2.2%)	6673	54.7	6.807	Journal of Antimicrobial Chemotherapy	5214	4318	5.790
5	Environmental Science and Pollution Research	122 (2.2%)	2487	20.4	4.223	Chemosphere	4893	2839	7.086
6	PloS One	119 (2.1%)	2837	23.9	3.240	Journal of Clinical Microbiology	4318	3287	5.948
7	BMC Infectious Diseases	105 (1.8%)	1052	10.02	3.090	Water Resech	3625	6368	11.236
8	Chemosphere	91 (1.6%)	5718	62.84	7.086	Environmental Pollution	3442	6448	6.807
9	Journal of Antimicrobial Chemotherapy	65 (1.2%)	3675	56.5	5.790	PloS One	3404	2178	3.240
10	Journal of Hazardous Materials	65 (1.2%)	2804	43.1	10.588	Applied and Environmental Microbiology	3287	2560	4.792
*Impact factors are retrieved from Web of Science

A total of 4334 institutions conducted antibiotic-related research in China, and the top 10 institutions contributed over 40% of the total number (Table 2). Chinese Academy of Sciences was ranked first with 471 papers published, which accounted for 8.4% +of the entire document. The institution actively cooperated with other 262 organizations (Fig. S4) and possesses the highest average citations (52.9/paper). Zhejiang University was the second most productive institution with 353 papers (6.3%), followed by Fudan University (4.1%), Shanghai Jiao Tong University (3.9%), and Peking University (3.8%). It is worth noting that Sun Yat-Sen University and China Agricultural University had relatively high Citations/N ratios but published fewer papers, indicating that these two institutions were also high-qualified.

3.3 Co-word Analysis

A total of 148 keywords with a frequency of over 50 were selected from the documents. The density visualization (Fig. 2A) was used to present the intensity of hotspots in the context of the colour spectrum. Words with warm colours like red and yellow have high frequency, and cold colours like blue and green indicate low frequency. Keywords with high intensity included antibiotic resistance, antibiotics, China, antimicrobial resistance, prevalence, ARGs, infections, Escherichia-coli, resistance and strains. These words present the primary trend of antibiotic studies in the past decades, primarily focusing on the prevalence of antibiotics and their related genes in the strains in infections (Cao et al., 2010; Qiao et al., 2013; Chinese et al., 2016; Li et al., 2016). Escherichia-coli (E.coli) is one of the keywords that was most frequently observed among the antibiotic papers. As a commensal bacteria, Escherichia-coli was ubiquitous in animals and humans thus usually accepted as indicator bacteria to monitor the antibiotic resistance in gram-negative bacteria population and modelling the emergence of antibiotic resistance (Roth et al., 2019). These bacteria are essential because they are associated with various infections in animals and humans, including intra-abdominal infections, diarrhoea, and oedema (Yang et al., 2004; Yang et al., 2013). Since the 1980s, high level of fluoroquinolone resistance was reported for E.coli isolate found in China (Wang et al., 2001). After that, the emergence, prevalence and spread mechanism of resistance genes (e.g. cell genes, mcr genes, Rmt genes, bla _CTX−M genes) in E.coli isolated from animals, patients and environments have been widely investigated (Chen et al., 2007; Li et al., 2011; Su et al., 2012; Quan et al., 2017).

The overlay map (Fig. 2B) from the recent five years (2017–2021) illustrates the development of hotspots for antibiotic studies in China. As shown in map, the lighter the colour of nodes, the later the average published the year of the keywords. In contrast, dark purple indicates the words could appear early, close to 2017. Node size presents the frequency of the keywords. As a result, the keywords were clustered into three groups to recognize various research areas based on the word level. Keywords in three clusters mostly appeard around 2016, with cluster 3 slightly later.

Research in cluster1 focuses more on the epidemiology, surveillance, management and treatment of the drug-resistance in infection caused diseases like sepsis, pneumonia and diarrhoea in China. It is interesting to find that the word COVID-19 is also included as the most updated keyword (average published year = 2020). During the pandemic in Wuhan, drug repurposing was used as an effective method in the absence of validated therapy. This method led to various types of antibiotics, including teicoplanin and azithromycin recognized as a possible alternative antiviral treatments for coronavirus (Drozdzal et al., 2020; Sargiacomo et al., 2020; Parasher, 2021). The mechanism of azithromycin is still not precise; however, for teicoplanin, it is assumed that the antibiotic can potentially influence the early stages of the viral replication cycle and inhibit viral detachment, thus preventing the release of viral RNA (Baron et al., 2020).

Meanwhile, antibacterial therapy was commonly prescribed for patients with severe COVID-19 in China (43%-100%), the United States (75%-100%) and Europe (88%-100%) (Huang et al., 2021). High concentrations of antibiotics are likely to be prescribed to patients during the pandemic, though the co-infection was observed to be relatively low (Langford et al., 2021). The intensity and distribution of antimicrobial resistance (AMR) caused by the abuse of antibiotics during and after the pandemic could be a new trend in antibiotic studies in China and other countries. It is reasonable to admit there could be challenging conditions, and effective management is urgently needed.

Cluster2 is a relatively larger cluster that required thorough exploration. The area mainly explored the prevalence of antibiotic resistance, virulence factors, biofilm formation and related functional genes in various pathogens origin from food animals or food products, especially retail meat. Except for E.coli from Enterobacteriaceae, we emphasized other genera, including salmonella (Chen et al., 2004) and staphylococcus aureus (Wu et al., 2018). Especially, mcr-1, the critical gene that emerged in China that we introduced, is the newest keyword within the cluster. As the largest antimicrobial consumer for livestock, it is estimated that the livestock industry could contribute over 30% of global antibiotics production by 2030 (Van Boeckel et al., 2015). It is worth worrying that resistance in commensal pathogens and the environment will increase in the future unless there is a nationwide government intervention.

The number of new keywords displayed in cluster3 is slightly higher when compared with other clusters. The cluster was mainly about the treatment of antibiotics, ARGs and their existence as contaminants in various environments (e.g., water, soil, and sediments). From the figure (Fig. 2B), it can be seen that several antibiotics, including tetracycline, sulfonamides, oxytetracycline and ciprofloxacin, were comprehensively investigated. The role of antibiotics in a natural environment started late in China. In our data, Xu et al. (2007b) was the first person in China who reported multiple antibiotics in a regional natural aquatic environment. In his paper, he investigated the condition of 9 antibiotics from 5 categories (ofloxacin, norfloxacin, roxithromycin, erythromycin, sulfadiazine, sulfadimidine, sulfamethoxazole, amoxicillin and chloramphenicol) at Victoria harbour and pearl river in the south of China, which had the highest antibiotics emission density (Zhang, 2015). Compared to antibiotics, the presence of ARGs in the natural environment was speculated earlier by Pei et al. (2006), where she reported them as emerging contaminants in the environment. The keyword ‘ARGs’ has a later average published in the year 2018. The first paper about ARGs in a regional natural environment (Haihe river) is from Luo (2010), who investigated ARGs in the Haihe River. Keywords like resistome and microbial communities are the most updated words in this cluster.

3.4 Document co-citation analysis

In Fig. 3A, the landscape view of the network was generated. A total of 132022 valid references were analyzed in DCA analysis. The network with 3555 nodes was divided into 384 clusters; the most significant five clusters accounted for about 27.6% of the total nodes (Table. S2). The network had a modularity of 0.9027, which was considered very high, and the specialities in mapping were clearly defined in terms of clusters. The average silhouette score was 0.9612, so the clustering result was highly credible. Areas in various colours can represent the time when co-citation links first appear. According to the spectrum, the darker the colour, the earlier the generated cluster. The most significant 13 clusters (Fig. 3A) were represented with antibiotic resistome (#3), recognized as unexplored areas. Antibiotic resistome is the collection of all antibiotic resistance genes in microorganisms. It comprises resistance elements in pathogenic and antibiotic-producing bacteria, and cryptic resistance genes, and precursor genes exist in non-pathogenic bacteria chromosomes (Wright, 2007). With the assistance of pan-microbiome sequencing methods, antibiotic resistome has become a new trend in antibiotic studies in China.

The milestones of antibiotic studies in China can be identified from references with intense citation bursts (Fig. 3C). Some of these articles have been previously mentioned. Globally, papers comparing antibiotics usage and ARGs distribution in China parallel with other countries are vital to demonstrate the severity of conditions (Zhu et al., 2017; Klein et al., 2018; Yang et al., 2018). It reveals that China had a low consumption rate, although the rate change, and the total antibiotic consumption was high compared with other countries. This result agrees with the study of Browne et al. (2021) that the consumption rate of human usage is only 8.0 DDD per 1000 habitants per day in China, which is lower than the global average of 14.3.

Nationally, in the past decades, antibiotics and ARGs in the aquatic environment were intensively studied not only in a single basin or bay like the Pearl river (Xu et al., 2007b), Haihe river (Luo et al., 2011), Yellow river, Liao river (Zhou et al., 2011), Yangze river and Bohai bay (Zou et al., 2011) but also included overall lakes (Liu et al., 2018a), rivers (Zhang, 2015) and seas (Li et al., 2018) in China. Antibiotic studies were also conducted and compared under various environmental conditions, including manure, underground water, soil and sewage (Xu et al., 2007a; Hu et al., 2010; Li et al., 2015; Qiao et al., 2018). As mentioned earlier, the highest cited paper from Zhang QQ ranked the first, and to our best knowledge, the only paper systematically studied the consumption and emission of antibiotics in China. However, it also discloses that the government's monitoring system of antibiotic resistance was minimal and lacked standardization in China. Also, China Antimicrobial Surveillance Network (CHINET) had fewer species, or genera monitored compared with many other high-income countries (e.g., KONIS from Korea, ANRESIS from Swiss) (Diallo et al., 2020). We suggest (1) the association between AR phenotypic surveillance with WGS, (2) an interconnection among human, animal (especially food animals) and environmental surveillance systems, (3) harmonization of antibiotic susceptibility tests with an international organization and access to a global network could further improve the network and reduce the problem of hysteresis quality.

Antibiotic studies are gradually moving into a phase of standardization and high-speed technological evolution. Standardized international terminologies like MDR (multidrug-resistant), XDR (extensively drug-resistant) and PDR (pan drug-resistant) were defined, and a joint initiative created the acquired resistance profiles by ECDC (European Centre for Disease Prevention and Control), CDC ( Centers for Disease Control and Prevention), and FDA (United States Food and Drug Administration) (Magiorakos et al., 2011). Similar to the co-word analysis results, various technologies are involved in antibiotic studies for different aims. Some technologies used early in the field include liquid chromatography and mass spectrometry (e.g. HPLC, MS/MS, LC-MS) used for the separation and quantification of antibiotics (Xu et al., 2007b; Zhou et al., 2011), and microbial typing technologies (e.g. Serotyping, PFGE, MLST, RAPD) play essential role in identifying sources and routes of infections and recognizing the genetic background of antibiotic-resistant isolates (Xu et al., 2007c; Fu et al., 2010; Qi et al., 2011). With the development of molecular technologies, especially next-generation sequencing (NGS), whole-genome sequencing (WGS) and metagenome sequencing are recognized as new trends during the evolution (Zhang et al., 2016). WGS is predicted to be the sole diagnostic and molecular epidemiological tool in identification, genetic characterization, and drug susceptibility testing (Ranjbar, 2014). In antibiotic studies, the method can potentially detect genetic determinants conferring AMR with different targets covered simultaneously. Opposed to other detection methods, it can add new target sequences to the database and perform in silico reanalysis with existing sequenced isolates (Anjum et al., 2017). While for metagenomic approaches, the method is more focused on the microbial DNA from environmental communities. In recent years, studies about the detection of ARGs with their transmission and proliferation mechanism in various environments remain elusive; however, this method can be solved (Peng et al., 2021). The technology could play an essential role in risk assessment and effectively reduce its concentration from the source.

In Fig. 3C, three bioinformatics tools or databases commonly used in NGS are represented as landmarks for antibiotic studies in China, which are ResFinder (2012), SPAdes (2012) and Prokka (2014). ResFinder is a web server with BLAST-based alignment to identify acquired ARGs from 12 classes. Pre-assembled and raw data from four platforms can be uploaded. Genes with specific similarities from 80–100% identity and the best matching genes are output. The tool is suitable for surveillance of AMR concerning acquired mechanisms (Zankari et al., 2012). While SPAdes is a de novo assembler focused on a single cell or standard (multicell) assembly, promoting bulge/tip removal algorithms, the method has a better performance than other assembly methods like Velvet and EULER-SR (Bankevich et al., 2012). After de novo assembly that transforms reads into contigs, Prokka could be the final step to annotate relevant genomic features within contigs. Seemann (2014) invented the tools with high throughput and privacy that can annotate a draft bacterial genome in 10 min. Better performance is also witnessed compared with other annotation tools like RAST and xBase2. In antibiotic studies, Prokka and ResFinder database could be utilized simultaneously to cross-validate ARGs and mobile genetic elements (Zhang et al., 2021).

3.5 Historical review and Future trends

All papers except the year 2022 are used in dual-map overlay to represent citation from source to its destiny. We deleted data from 2022 as it is too few to show the trend in a whole year.

In Fig. 4, spine waves in different colours are used to represent the citations, which are mainly green, orange and yellow in our case. Each wave starts from a citing journal on the left to the cited journal on the right of the base map. Z-score normalization and F value were calculated to present the most significant changes as thick belts. Labels on the wave indicate the corresponding disciplines change from the citing to the cited discipline. In this study, citing journals focused on veterinary, animal and science (cluster7) mainly had references from fields like environmental, toxicology, nutrition (cluster2 right), molecular, biology and genetics (cluster8), and health, nursing, and medicine (cluster5 right). Citing journals research on molecular, biology and immunology (cluster4) usually cite journals within the same field (cluster 8). Journals from the field of medicine, medical and clinical (cluster2 left), however, cited articles from various disciplines, including environmental, toxicology, nutrition (cluster2 right), molecular, biology and genetics (cluster8) and health, nursing, and medicine (cluster5 right). The main research areas are in accord with our former outcomes. Cluster 8 constantly appears as the cited area, which is not surprising as molecular biological technologies are extensively used in various fields, especially in antibiotic studies. Cluster 7 veterinary, animal and science also consisted of most journals about the environment (e.g. Environmental International). We assume this is due to vital veterinary antibiotics like sulfonamides, tetracyclines, and fluoroquinolones being widely used in the Chinese agricultural sector (Collignon and Voss, 2015). As the primary consumption market in China, large amounts of these antibiotics flow to various environments and become dominant contaminants.

The zoomed red trajectories of citing and cited journals were computed at the bottom of the figure. These trajectories are a continuous changing of the position of the weight centre of centroids of clusters and can be seen as the footprint of antibiotic studies in China. It is clear to see that there were substantial fluctuations at the beginning of antibiotic studies in China among molecular, biology, immunology (dark yellow) and medicine, medical, clinical (green), but finally tended to the direction of veterinary, animal and science (light yellow) were mainly focused on environmental science. On another side of cited journals, the weight centre primarily focused on molecular, biology, and genetics (light pink) without a noticeable trend.

We predict that in future years, documents of antibiotic studies will continuously develop in the area of veterinary, animal and science, and the environmental science related core and multidisciplinary journals to become predominant in the future. For the intellectual base, molecular, biology, genetics and environmental, ecotoxicology, nutrition will become essential and dominate in future years.

The position that connects different parts of the network tends to be exposed to various perspectives and opinions. Papers on structural holes usually have the potential to make profound impacts on the global structure of the research field. SVA analysis enabled us to identify the creative papers once they are published by comparing them with a baseline network formed with literature prior to publication of those articles. Table 3 lists ten documents with the most substantial transformative potential in terms of centrality divergence (C_KL) in the recent five years, and these papers could be highly cited in future.

Among the ten papers, four reviews systematically introduced the migration, influence factors and ecological risk assessment of antibiotic resistance in various natural habitats, especially aquatic environments (Gao et al., 2018; Qiao et al., 2018; Yang et al., 2018; Zhao et al., 2018a). Food science and environmental science are the main study areas for the rest of the articles. Among the three environmental studies, one crucial feature shared was the usage of multiple methods for a comprehensive understanding at spatial and temporal levels. Except for novel sequencing technologies like 16S rRNA sequencing (typically present taxonomic composition of the microbial community), metagenomic shotgun sequencing and q-PCR, other methods like LC-MS/MS microbial source tracking (MST) are also implemented. Through various analyses, series questions include the source of AR, host of ARGs, dissemination mechanisms with its controlling factors of antibiotic resistome and the risk proposed are clarified. While for the two food science studies, whole-metagenome shotgun sequencing is also applied for genes research. Different from environmental articles, the feeding industry is a critical source of antibiotics and ARGs, and therefore, the condition of the source and its migration mechanisms from food animals to humans or the environment should have more attention.

One interesting fact found in the analysis is an article with 0 citations had the highest centrality divergence (which indicates high structural variation). In the paper, a new online platform invented by Naumov et al. (2021) called 'COVIDomic' is designed to facilitate a large amount of data collected from covid-19 patients. Through an analytical workflow of microbial pathogens community analysis, ARGs expression of samples can be explored to evaluate the overall antibiotic resistance of the host-microbial community. Corresponding with the presence of the word "covid-19" in co-word analysis, the paper is a pioneering research on the impact and risk of antibiotic usage. A globally antibiotic usage condition could be drawn with more data uploaded into the platform.

Table 3

Top10 papers with strongest transformative potential in terms of centrality divergence
Citation	ΔM	CL	C_KL	E	Title of the citing document	References
0	0	-2.63	0.15	0.69	COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity	(Naumov et al., 2021)
488	97.87	-6.58	0.11	1.56	Review of antibiotic resistance in China and its environment	(Qiao et al., 2018)
4	83.55	-6.91	0.1	0.96	More diversified antibiotic resistance genes in chickens and workers of the live poultry markets	(Wang et al., 2021)
35	86.87	-16.53	0.09	0.5	Complex migration of antibiotic resistance in natural aquatic environments	(Gao et al., 2018)
27	88.84	-22.42	0.09	0.56	Antibiotic resistance genes in China: occurrence, risk, and correlation among different parameters	(Zhao et al., 2018a)
43	81.08	-19.79	0.08	0.79	Antibiotics and antibiotic resistance genes in global lakes: A review and meta-analysis	(Yang et al., 2018)
21	93.83	-22.27	0.08	1.55	Metagenomic analysis revealed the prevalence of antibiotic resistance genes in the gut and living environment of freshwater shrimp	(Zhao et al., 2018b)
205	96.14	-14.02	0.08	1.2	Urbanization drives riverine bacterial antibiotic resistome more than taxonomic community at watershed scale	(Peng et al., 2020)
23	89.11	-26.15	0.08	0.93	Characterization and source identification of antibiotic resistance genes in the sediments of an interconnected river-lake system	(Chen et al., 2020)
10	88.8	-14.27	0.08	1.3	Homogeneous selection drives antibiotic resistome in two adjacent sub-watersheds, China	(Hu et al., 2020)
*ΔM = modularity change rate
* CL = cluster linkage
* C_KL = centrality divergence
* E = Entropy

This research reported a systematic review of the research related to antibiotics in China in the latested three decades based on the information of keywords, authors, journals, institutions and co-citations from 5559 published references in past three decades. Our results indicate that only a few authors constantly contribute to the area, and there is an imbalance in the quality and quantity of papers. A growing interest in antibiotic studies and collaboration among institutions could be observed in the future. In co-word analysis, COVID-19, mcr-1 and antibiotic resistome are the three most updated words, while food science, clinical research and environmental studies are the three main research directions in the field. Molecular biology, genetics and environmental, ecotoxicology, and nutrition are recognized popular areas in upcoming years. In DCA analysis, antibiotics and ARGs in aquatic environments, terminology standardization and evolution of technologies were recognized as milestones in this research in China. Combined with SVA analysis, a relatively accurate prediction of future research could be drawn, and researchers should pay closer attention to the following areas in the coming years:

Comprehensive studies of ARGs dissemination in various environments both in temporal and spatial scales. Diverse novel technologies should be used to figure out the appropriate source, migration routes, mechanisms, the risk caused during the process and methods to migrate the adverse impact. Especially, measurements taken in wastewater management need to be improved. As wastewater treatment plants were not ideal for affording the removal of ARGs, technologies that include artificial wetlands, membrane bioreactors, and advanced oxidation processes should be applied in the treatment stage. Moreover, standards-setting limitations of antibiotics/ARGs emission should be performed.

The surveillance network of AR will be more critical in the future, especially in combining sources (animals, clinical facilities) and sinks (environments, humans). Except for discovering new resistant isolates and ARGs from sources, efforts should be made on issues, including the condition in the sources and their surrounding environments, workers who have a close connection, and how sources migrate to the sinks.

Management of AR after COVID-19 will become an essential part of future studies. When patients are critically ill and the diagnosis of potential bacterial superinfection is uncertain, antibiotics are unavoidably prescribed as a life-saver. Fundamental problems include defining an appropriate antibiotic dose during the treatment, rebuilding surveillance and management systems when the antibiotic stewardship programmes have declined, and finally, reducing the consequences of AR after spreading into the environment.

Ethical Approval

The publication is approved by the responsible authorities where the research was carried out. We promise that the paper is original and will not be published elsewhere in any form and in any language without the consent of the Publisher.

Consent to Publish

All authors have approved this submission to your esteemed journal.

Authors Contributions

All authors contributed to the study concept and design. The idea for the article was contributed by Professor Songhe Zhang. The literature research, data analysis and the draft of the article was completed by Tong Yu. Dr. Adharsh Rajasekar critically revised the word. All author read and approved the final draft.

Funding

This work was financially supported by the grants from the National Natural Science Foundation of China (No. E51879084 and E51579075).

Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

Availability of data and materials

The datasets used or analysed during the current study are available from the corresponding author on reasonable request.

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A Decennials Study of the Trend of antibiotics studies in China

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Abstract

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1. Introduction

2. Methodology

3. Result And Discussion

3.1 Background Of Antibiotics Studies In China

3.1.1 Contribution of Authors

3.2 Contribution of Journals and Institutions

3.3 Co-word Analysis

3.4 Document co-citation analysis

3.5 Historical review and Future trends

4. Conclusion

Declarations

References

Supplementary Files

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Journal Publication

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