Major depressive disorder (MDD) is a common but serious neuropsychiatric disorder that can greatly affect the patients’ quality of life (Martins-de-Souza, 2014; Zhu et al., 2020; Liu et al., 2021; Tian et al., 2021). It is mainly characterized by emptiness or hopelessness, loss of interest, and sleep disturbances (Rana et al., 2021). Previous studies reported that MDD was closely related to hippocampal atrophy, disorder of the hypothalamic–pituitary–adrenal (HPA) axis, and reduction of glial cells in the prefrontal cortex (Ongür et al., 1998; Campbell and Macqueen, 2004; Pariante and Lightman, 2008). However, commonly accepted theories about the pathogenesis of MDD are still not available. Meanwhile, the first-line treatment according to these theories can only alleviate symptoms in about half of MDD patients (Al-Harbi, 2012), and there are no validated biomarkers for objective diagnosis of MDD nowadays. Thus, it is urgently needed to further study the pathogenesis of MDD from new perspectives.

Gut microbiota plays an important role in maintaining the host’s health, and many researchers pay attention to the cross talk between the gut and brain (Han et al., 2020; Qiao et al., 2020; Kovács et al., 2021; Khoshkam et al., 2021). Mounting evidence shows that gut microbiota can affect the host’s brain functions and behaviors via the “microbiota–gut–brain” axis (Chen et al., 2021; Rajput et al., 2021; Ding et al., 2021; Dong et al., 2021). In our previous work, we found significant differences in gut microbiota compositions between MDD patients and healthy controls (HC) (Chen et al., 2020; Bai et al., 2021), and these differences were specifically relative to bipolar disorder and schizophrenia (Zheng et al., 2019; Zheng et al., 2020). Other researchers also found that some bacterial taxa, such as Flavonifractor and Faecalibacterium, changed in patients with depression (Coello et al., 2019; Zhou et al., 2020; Coello et al., 2021). Using an animal depression model, we reported that gut microbiota could induce depression-like behaviors by regulating the host’s metabolism (Zheng et al., 2016) and that glycerophospholipid metabolism might be the vital node between microbiota and depression (Tian et al., 2022). These findings suggested that further exploring the role of gut microbiota in the onset of depression may be helpful for revealing the pathogenesis of MDD.

Many metabolites produced by gut microbiota are closely related to health (Lu et al., 2021; Zhong et al., 2021; Xie et al., 2021). Short-chain fatty acids (SCFAs), as the main products of gut microbiota, have been found to change in many diseases such as cardiovascular disease and autism (Chambers et al., 2018; Tran and Mohajeri, 2021). Our previous studies found some differential microbial metabolites in the urine and plasma of MDD patients (Zheng et al., 2013; Zheng et al., 2013; Chen et al., 2015). Moreover, we found differential urinary and plasma metabolites related to the severity of MDD (Liu et al., 2015; Chen et al., 2017). Considering the close relationships between metabolites and gut microbiota in MDD, we conducted this study to explore whether the differences in gut microbiota compositions were also related with the severity of MDD.

This study was conducted to find the divergent microbes of different MDD severity. The results showed that there were 36 and 27 differential genera in moderate and severe MDD patients, respectively. The differential genera in moderate and severe MDD patients mainly belonged to three (Firmicutes, Actinobacteriota, and Bacteroidota) and two phyla (Firmicutes and Bacteroidota), respectively. Meanwhile, one specific covarying network from phylum Actinobacteriota was identified in moderate MDD patients. In addition, the moderate and severe MDD patients shared no differential genera that were significantly correlated with the HDRS score. Therefore, these findings suggested that although moderate and severe MDD patients shared some common differential genera, the two groups had significantly different microbial signatures.

Currently, clinicians still use the structured clinical interview rather than objective laboratory tests to diagnose MDD. However, the interview method often results in a certain percentage of misdiagnosis (Mitchell et al., 2009) due to the highly heterogeneous of clinical presentation of MDD. One promising way to markedly increase the accuracy of diagnosis is to identify disease biomarkers for objectively diagnosing MDD. In recent decades, much work has been done to identify potential biomarkers for MDD (Dmitrzak-Weglarz et al., 2021; Bai et al., 2021; Huang et al., 2022; Travica et al., 2022). However, few studies have taken the severity of MDD into consideration. In our previous studies, the differential urinary and plasma metabolites related to the severity of MDD were observed (Liu et al., 2015; Chen et al., 2017). Here, we provided an interesting method to identify potential biomarkers for MDD. A panel consisting of five consistently changed genera was found to have fair efficacies in diagnosing MDD patients from HCs.

Gut microbiota could be influenced by many factors, such as dietary habit and antibiotic agents (Farag et al., 2020; Khan et al., 2020; Dordević et al., 2021; Liu et al., 2021). Madison et al. reported that dietary habit could affect the gut microbiota compositions independently or in conjunction with stress (Madison and Kiecolt-Glaser, 2019). Lv et al. found that there was a close relationship between BMI and gut microbiota compositions in Chinese male college students (Lv et al., 2019). Duan et al. observed that the gut microbiota compositions were different in cynomolgus macaques with different ages (Duan et al., 2019). Our previous study found the differential gut microbiota compositions between young and middle-aged MDD patients (Chen et al., 2020). In the present study, our findings further suggested that the gut microbiota compositions could also be affected by the severity of MDD. These results might provide a novel clue for understanding the role of gut microbiota in the onset of depression. However, only gut microbiota at the genus level was analyzed here. Therefore, our identified potential microbial biomarkers—although very promising—were preliminary results and need further validation.

Firmicutes and Bacteroidetes are the two phyla of dominating bacteria in human gut microbiota. Zheng et al. found that the relative abundance of Bacteroidetes was significantly changed in MDD patients compared with HCs (Zheng et al., 2016). Jiang et al. reported that both the relative abundances of Firmicutes and Bacteroidetes were significantly disordered in MDD patients compared with HCs (Jiang et al., 2015). In our previous study, we found that compared with HCs, the relative abundance of Bacteroidetes was significantly increased and decreased in young and middle-aged MDD patients, respectively, and the relative abundance of Firmicutes was only found to be significantly changed in young MDD patients (Chen et al., 2020). In this study, we observed that the differential genera in moderate and severe MDD patients mainly belonged to three (Firmicutes, Actinobacteriota, and Bacteroidota) and two (Firmicutes and Bacteroidota) phyla, respectively. These results indicated that the gut microbiota compositions could be affected by many factors, and further studies on the associations between MDD and gut microbiota should minimize the influence of confounding factors.

The shared differential genus Collinsella by two MDD groups is an important intestinal bacterium to produce ursodeoxycholic acid. Ursodeoxycholic acid has antioxidant and anti-apoptotic effects and can suppress pro-inflammatory cytokines like IL-2 and TNF-α (Hirayama et al., 2021). The close relationships between MDD and inflammation have been reported in many previous studies (Leonard, 2018; Colasanto et al., 2020). Another shared differential genus Faecalibacterium is an important intestinal bacterium to produce butyric acid. Butyric acid is a major short-chain fatty acid (SCFA) produced by gut microbiota (Sun et al., 2021). SCFAs are speculated to play an important role in the cross talk between the gut and brain. Our previous study found associations between disordered hypothalamus neurotransmitters and fecal SCFAs in depressed mice (Wu et al., 2020). These results showed that the identified shared differential genus were worthy of further exploring.

Previous studies reported that the dominant taxa were different in the different phases of the life cycle (Lim et al., 2015; Vemuri et al., 2018). Our previous study found that there were age-specific differential changes on gut microbiota composition in MDD patients (Chen et al., 2020). In this study, we identified three significantly decreased and one significantly increased genus in severe MDD patients compared with moderate MDD patients. Three of them (Catenibacterium, Dorea, Megamonas) belonged to the phylum Firmicutes. These results indicated that the continuing changes of gut microbiota in moderate MDD patients, especially phylum Firmicutes, might contribute to the deterioration of depression. Therefore, developing personalized treatment methods to timely treat moderate MDD patients might be able to alleviate or delay the progress of depression.

Many studies have reported the microbial markers of depression (Jiang et al., 2015; Chen et al., 2018; Zhou et al., 2020; Yang et al., 2020). Zhou et al. found that gut microbiota-based biomarkers, such as Faecalibacterium and Butyricicoccus, might be helpful for the diagnosis and treatment of postpartum depressive disorder patients (Zhou et al., 2020). Here, Faecalibacterium was also identified as a potential biomarker for MDD. Another study reported that a combinatorial marker panel consisting of bacterial species and fecal metabolite markers could effectively discriminate MDD from HC (Yang et al., 2020). Our previous study found that the suitability of Actinobacteria and Bacteroidia as the sex-specific biomarkers for diagnosing MDD was worthy of further exploring (Chen et al., 2018). Jiang et al. observed that Alistipes and Faecalibacterium might be potential biomarkers for MDD patients (Jiang et al., 2015). Here, Collinsella and Eggerthella belonged to phylum Actinobacteriota and Alistipes belonged to phylum Bacteroidota were identified as potential biomarkers for MDD. Although these results showed a potential and novel method for objective diagnosis of depression, further studies were warranted to evaluate the suitability of gut microbiota as a biomarker for depression.

Several limitations should be mentioned here. Firstly, the number of subjects in each group was relatively small, which requires future studies to validate and support the conclusions. Secondly, although the potential effects of main confounding factors (age, BMI, sex ratio) were eliminated, the effects of other potential factors, such as family history of psychiatric diseases, host genetics, smoking, and dietary habit, were not explored here; thus, future studies were needed to assess the effects of these factors. Thirdly, all the included subjects came from the same place, and thus there might be ethno-specific biases, which could limit the applicability of our conclusion. Fourthly, due to technical reasons, the identification of gut microbiota at the species level was unsuccessful. Therefore, it might also be meaningful to further investigate the differential gut microbiota compositions at the species level. Fifthly, we did not analyze the functions of differential gut microbiota related to the severity of MDD, which was worthy of further exploring using whole-genome sequencing (WGS) or phylogenetic investigation of communities by reconstruction of unobserved states (PICRUST). Sixthly, the “healthy human microbiota” is only a theoretical phenomenon. Due to the complexity of assessing the health status of gut microbiota, the “healthy human microbiota” has not yet been defined. Thus, the microbial biomarkers should be cautiously interpreted. Seventhly, although the sensitivity analysis showed that the results obtained by excluding these 21 MDD patients were similar to the original results, we did not know whether 1 month was enough to remove the effects of antidepressive treatments on gut microbiota; thus, future studies should recruited drug-naïve MDD patients to evaluate our results.

In conclusion, this study found that there were divergent microbial phenotypes between moderate and severe MDD patients. Totally, 36 and 27 differential genera in moderate and severe MDD patients, respectively, were identified. One specific covarying network from phylum Actinobacteriota was identified in moderate MDD patients. In addition, five differential genera (Collinsella, Eggerthella, Alistipes, Faecalibacterium, and Flavonifractor) held promise as the potential biomarkers for diagnosing MDD. Our results may also be helpful for further exploring the role of gut microbiota in the pathogenesis of depression.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/, PRJNA806486.

The studies involving human participants were reviewed and approved by Ethical Committee of Chongqing Medical University. The patients/participants provided their written informed consent to participate in this study.

QZ, J-JC, and PX conceived and designed the study; QZ, YW, and W-HS participated in data collection. J-JC and C-JZ analyzed the data. QZ, J-JC, and PX prepared the paper. All authors have read and approved the final manuscript.

This work was supported by the National Key Research and Development Program of China (2017YFA0505700), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT320002), the Natural Science Foundation Project of China (81820108015, 81701360), the Natural Science Foundation of Chongqing (cstc2021jcyj-msxmX0084), the Science and Technology Research Program of Chongqing Municipal Education Commission (Grant No. KJQN202100420), and the Chongqing Yuzhong District Science & Technology Commission (20190115).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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