Participants
Seventy depressed patients who attended the First Hospital of Shanxi Medical University from December 2020 to January 2021 were selected as the depression group. According to medical history, clinical manifestations, and laboratory tests, the following diagnostic criteria were used: (1) diagnostic criteria in the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) [27] were met; (2) symptoms were mainly depressed mood with at least four of the following: unpleasant feelings or loss of interest; fatigue or loss of energy; psychomotor retardation or agitation; feelings of guilt, self-blame, or low self-esteem; reduced ability to think or difficulty with cognitive association; self-injury, suicidal behavior, or recurrent thoughts of death; sleep disorders, such as early awakening, insomnia, or excessive sleep; decreased libido; decreased sexual desire; decreased sleepiness; and significant weight loss or decreased appetite; and (3) a Hamilton Depression Scale score ≥ 20. Inclusion criteria were meeting the above diagnostic criteria as confirmed by our specialist, duration of illness ≥ 2 weeks, and age ≥ 18 years. Exclusion criteria were underlying diseases such as hypertension, coronary heart disease, metabolic diseases, liver cirrhosis, inflammatory bowel disease, irritable bowel syndrome, and other psychiatric diseases, such as bipolar disorder, persistent mood disorder, and manic episodes. All enrolled subjects received antidiarrheal drugs, bloating agents, probiotics, antispasmodics, antibiotics, and other medications within the 30 days prior to sample collection.
Twenty-two healthy individuals who underwent health check-ups at the First Hospital of Shanxi Medical University from December 2020 to January 2021 were selected as healthy controls. The inclusion criteria were no chronic diarrhea, no special dietary preferences, and no underlying diseases, such as hypertension, diabetes mellitus, hyperlipidemia, etc. Exclusion criteria were abnormal mental status, menopausal syndrome, neurosis, long-term insomnia, or antibiotic treatment within two weeks before the physical examination.
Both groups of study subjects voluntarily enrolled in this study, and informed consent form was obtained from all participants. The subject recruitment process is illustrated in Figure 1. There was no statistical difference between the two groups in terms of general information (P > 0.05). This study was reviewed and approved by the Medical Ethics Committee of the First Hospital of Shanxi Medical University.
Stool collection and DNA extraction
Stool sample collection was completed within 24 hours of admission for the inpatients in the depression group. Approximately 15g of stool were collected in a sterile plastic box, numbered, registered, and stored in a refrigerator at -80 °C. In the healthy control group, stool samples were collected upon completion of a physical examination. Stool was collected and processed using the same method as in the depression group. After all stool specimens were collected, DNA was extracted using a stool DNA extraction kit (StoolGen DNA kit, Beijing Youji Technology Co., Ltd.). The extracted total DNA was tested for integrity using an agarose gel electrophoresis instrument (Beijing Liuyi Company, DYY-6C).
DNA amplification
We amplified different regions of the bacterial 16S rDNA gene and other functional genes using polymerase chain reaction (PCR). Primers were designed to amplify single or multiple variable regions of the rRNA gene using conserved regions of ribosomal RNA to sequence and analyze microbial diversity. In this experiment, the highly variable V3-V4 region of the bacterial 16S rRNA gene with a length of approximately 468 bp was used for sequencing. PCR amplification was performed using bacterial 16S rDNA V3-V4 region-specific primers, 338F (5'-ACTCCTACGGGAGGCAGCA-3') and 806R (5'- GGACTACHVGGGTWTCTAAT-3'). The barcode in the preprimer is a 7-base oligonucleotide sequence used to distinguish different samples from the same library. PCR amplification was performed using the Q5 DNA high fidelity polymerase (NEB, M0491L), and the amplification reaction system are shown in Table 1.
Table 1 16S rDNA V3-V4 region amplification reaction system
Ingredients
|
Volume (μL)
|
Q5 high-fidelity DNA polymerase
|
0.25
|
5*Reaction Buffer
|
5
|
5* High GC Buffer
|
5
|
dNTP (10 mM)
|
2
|
Template DNA
|
2
|
Forward primers (10uM)
|
1
|
Reverse primer (10uM)
|
1
|
water
|
8.75
|
After the required components of the PCR reaction were configured, the template DNA was pre-denatured at 98°C for 30 seconds on the PCR instrument in order to denature the template DNA to a sufficient degree prior to entering the amplification cycle. In each cycle, the sample was held at 98°C for 15 seconds to denature the template, then the temperature was lowered to 50°C and held for 30 seconds to fully anneal the primers to the template. Then, the sample was held at 72°C for 30 seconds to extend the primers over the template and synthesize the DNA. This method makes up a single PCR cycle. The cycle was repeated 25-27 times to allow a large accumulation of amplified DNA fragments. Finally, the product was kept at 72°C for 5 minutes to allow complete extension and was stored at 4°C. The amplification results were subjected to 2% agarose gel electrophoresis, and the target fragments were cut and recovered using the Axygen gel recovery kit.
PCR product quantification and mixing
The PCR products were quantified on a microplate reader (BioTek,FLx800T) using the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen,p7589) and then mixed according to the amount of data required for each sample.
Library construction
(1) Library construction was performed using the TruSeq Nano DNA LT Library Prep Kit (Illumina). End repair was first performed using the End Repair Mix2 feature of the kit to excise the base protruding from the 5' end of the DNA and fill in the missing base at the 3' end, while adding a phosphate group at the 5' end. The following method was used:
①The mixed DNA fragments (30 ng) were rehydrated to 60 μL and 40 μL with the End Repair Mix2 feature.
②The DNA fragments were mixed with micro sampler blast and incubated on a PCR instrument at 30°C for 30 minutes.
③The end repair system was purified using BECKMAN AMPure XP beads and eluted with 17.5 μL of a resuspension buffer.
(2) Adenine bases (A) were added at the 3' end of the DNA sequences to prevent self-connection of the DNA fragments and to ensure that the DNA is connected to a sequencing junction with a prominent thymine base (T) at the 3' end using the following method:
①12.5 μL of A-Tailing Mix was added to the fragment-selected DNA.
②The samples were mixed well with a micro sampler blow, placed on a PCR instrument, and incubated with the following temperature schedule: 37°C for 30 minutes, 70°C for 5 minutes, 4°C for 5 minutes, and 4°C indefinitely.
(3) A splicing agent with a specific label was added. This procedure was performed to allow final hybridization of the DNA to the flow cell as follows:
①2.5 μL of a resuspension buffer, 2.5 μL of a ligation mix, and 2.5 μL of a DNA adapter index were added to the system which A had been added.
②The solution was mixed with a micro sampler blow and incubated at 30°C for 10 minutes on a PCR instrument.
③ 5 μL of Stop Ligation buffer was added to the mixture.
④The system with added connectors using BECKMAN AMPure XP beads was purified.
(4) The DNA fragment that has been coupled by PCR was amplified and, the PCR system using BECKMAN AMPure XPbeads was purified.
(5) Final fragments were selected and, the library was purified using 2% agarose gel electrophoresis.
Library quality control and sequencing
(1) Library quality control (QC) and quantification was performed using the following method: a 1 μL sample of the library was taken, and the library was subjected to 2100 QC using the Agilent High Sensitivity DNA Kit on an Agilent Bioanalyzer (Agilent Technologies, USA) machine; qualified libraries should have a single peak and no junction. The libraries were quantified using the Quant-iT PicoGreen dsDNA Assay Kit on a QuantiFluor fluorometer (Promega); qualified libraries should have a calculated concentration of 2nM or more.
(2) The library was sequenced using the following method: for qualified libraries, 2×250 bp double-end sequencing was performed on a MiSeq machine using the MiSeq Reagent Kit V3 (600cycles). Libraries on the machine (Index not reproducible) were gradient diluted to 2nM and mixed in proportion to the amount of data required. The mixed libraries were denatured to single strands using 0.1N NaOH for up-sequencing. The amount of uploaded library was controlled to be between 15 and 18 pM. The data obtained from the down machine were subjected to bioinformatics analysis.
Bioinformatics analysis
The off-board data were filtered, and the original sequencing data were processed using an internally written program to filter out low-quality sequencing fragments (reads). The remaining high-quality clean data were used for post-analysis, with the following steps:
(1) 30 bp was set as the window length. If the window began truncating read end sequences, we remove the final read length below 75% of the
(2) The Fast Length Adjustment of Short reads (FLASH) (v1.2.11) software was used the overlap the DNA fragments and assemble pairs of reads obtained from the double-end sequencing into a single sequence, obtaining high complexity reads.
(3) After obtaining the operational taxonomic unit (OTU) representative sequences, the OTU representative sequences were compared with the Greengene_2013_5_99 database using RDP Classifier (v2.2) software.
(4) The OTUs were annotated with their respective species and compared.
Analysis of microbial community diversity and abundance in the gut
The generated OTU information was used to analyze the community diversity and abundance variation of the gut microflora. Alpha diversity values of the samples were calculated using Mothur (v1.31.2) software, including the observed species index, Chao index, ACE index, Shannon index, and Simpson index, where the observed species index, Chao index, and ACE index reflected the abundance of the community in the samples. The Shannon index and the Simpson index reflected the diversity of the community. In addition, the relative abundance of each OTU in each sample was calculated based on the abundance of each OTU in each sample. This abundance information was used to carry out a principal component analysis (PCA) of the OTUs by analyzing the composition of the different sample OTUs (97% similarity) to reflect the differences and distances of samples; PCA uses variance decomposition to reflect the differences of multiple sets of data on a two-dimensional coordinate graph. The axes reflect the maximum variance value of two eigenvalues; if two samples are closer on the graph, it means that the composition of these two samples are more similar.
Species classification of the OTUs was performed, and heatmap clustering analysis was performed at several taxonomic levels of phylum, order, family, genus, and species, respectively, by comparison with the database. Differences in microbial community abundance between samples from the depression and healthy control groups were examined statistically, and the significance of the differences was assessed using the false discovery rate (FDR), from which the species responsible for the differences in the composition of the two groups could be screened. We used R software (rank sum test, Fisher's exact test, t-test, variance test) for the analysis of significant differences between the groups, and p-value correction was performed by p.adjust in the R (v3.1.1) package, using the Benjamini-Hochberg (BH) correction method.