Comparative Proteomic Analysis of Leptospira Interrogans Serogroup Icterohaemorrhagiae Human Vaccine Strain and Epidemic Isolate of China

Background: Leptospira interrogans serogroup Icterohaemorrhagiae is the predominant pathogen causing leptospirosis in China and is still used as the vaccine strain for the current human inactivated vaccine. Unlike the clade ST17, which is distributed worldwide, ST1 is the most prevalent in serogroup Icterohaemorrhagiae in China. Purpose and Methods: To further characterize leptospiral pathogens, isobaric tags for relative and absolute quantitation and parallel reaction monitoring were used to analyze differences at the proteomic level between serogroup Icterohaemorrhagiae vaccine strain 56001 (ST1) and circulating isolate 200502 (ST17) from different periods. Results: Two hundred and eighty-one proteins were differentially expressed between ST17 and ST1, of which 166 were upregulated (>1.2 fold change, P < 0.05) and 115 (>1.2-fold change, P < 0.05) were downregulated. Function prediction revealed that nine upregulated proteins were outer membrane proteins, including several known immunogenic and/or virulence-related proteins, such as ompL1, LipL71 and LipL41. Furthermore, important expression differences in carbohydrate, amino acid, and energy metabolism and transport proteins were identied between ST1 and ST17, suggesting that these differences may reect metabolic diversity and the potential of the pathogens to adapt to different environments. Conclusion: In summary, our ndings provide insights into better understanding the component strains of the Chinese human leptospirosis vaccine at the proteomic level. Additionally, these data facilitate evaluating the mechanisms by which pathogenic Leptospira species adapt to the host environment. Icterohaemorrhagiae study aimed to determine the differences at the proteomic level between two strains of Leptospira serogroup Icterohaemorrhagiae from different periods: 200502, a cluster CC17 strain (ST17) isolated in Sichuan, China in 2005 and 56001, a cluster CC1 strain (ST1) isolated in Sichuan in 1958 used as one of the vaccine strains. Isobaric tags for relative and absolute quantitation (iTRAQ) and parallel reaction monitoring (PRM) were used to compare protein expression differences in the global whole-cell proteome to shed light on the adaptation of current epidemic strains. Scientic), data-dependent with a full MS scan range from m/z, full scan resolution of 70,000, MS/MS scan resolution of 17,500, MS/MS scan with a minimum signal threshold 1E+5, and isolation width of 2 Da. To evaluate mass spectrometric performance of the iTRAQ-labeled samples, two MS/MS acquisition modes and higher collision energy dissociation (HCD) were employed. Furthermore, to optimize the MS/MS acquisition eciency of HCD, normalized collision energy was systemically examined and stepped by 20%. important proteins, several known immunogenic and/or virulence-related OMPs and lipoproteins, were found in the most prevalent circulating ST17 strain, providing critical insights for the development of whole-cell and recombinant leptospirosis vaccines. Furthermore, the differential metabolism-related proteins identied may be key contributors to the tness difference between the two ST clusters.


Introduction
Leptospirosis is one of the most important but neglected zoonotic diseases caused by pathogenic Leptospira species [1]. It is estimated that there are approximately 1 million human leptospirosis cases worldwide each year, with 58,900 deaths [2]. In China, leptospirosis has been a reportable disease since 1955. Ten large outbreaks of leptospirosis, with an incidence of over 10 cases per 100,000 people, have occurred since 1990 [3]. In addition to improving sanitation and water conservation, vaccination of at-risk populations should be conducted to prevent and control leptospiral infections. It has been reported that leptospirosis incidence has been maintained at less than 1 case per 100,000 people since 1997, with only 214 and 297 cases reported in 2019 and 2020, respectively. Regardless, leptospirosis remains endemic and small local outbreaks still occur in the southern provinces of China [4][5][6].
A multivalent, inactivated leptospirosis vaccine is currently used to immunize high-risk populations in endemic regions in China. The vaccine contains L. interrogans serogroups Icterohaemorrhagiae, Canicola, Grippotyphosa, Autumnalis, Pomona, Australis, and Hebdomadis, covering more than 80% of the serogroups of the endemic strains in China [3,7]. Due to the serogroup-speci c immunity induced by the inactivated leptospirosis vaccine, it is important to monitor pathogenic Leptospira epidemiology to guide vaccine production [7]. There is evidence that Icterohaemorrhagiae has been the predominant serogroup in China in recent history [8]. For example, of the 341 Leptospira strains isolated from 2002 to 2015 in China, 61.1% belonged to serogroup Icterohaemorrhagiae [9]. Although the predominant serogroups have been consistent in China [9,10], whether there occur differences between the current epidemic isolates and the vaccine strains isolated in the 1950s from the same serogroup is unknown.
Indeed, recent studies have reported the predominance of the clade ST1 in the serogroup Icterohaemorrhagiae in China in the past decades [11]. In contrast, ST17 has been the most prevalent clone globally [12]. It is hypothesized that in addition to genetic differences, the current predominant cluster ST17 strains have increased protein expression, providing them with increased tness and selective advantage. Furthermore, it has been reported that leptospirosis-associated severe pulmonary hemorrhagic syndrome (SPHS) associated with fatality rates of >50% in Brazil was caused by L. interrogans serogroup Icterohaemorrhagiae serovar Copenhageni, which also caused non-SPHS leptospirosis cases in China [13]. This indicates that the appearance of SPHS may be associated with the introduction or emergence of a clone that has enhanced virulence within this serovar.
Therefore, this study aimed to determine the differences at the proteomic level between two strains of Leptospira serogroup Icterohaemorrhagiae from different periods: 200502, a cluster CC17 strain (ST17) isolated in Sichuan, China in 2005 and 56001, a cluster CC1 strain (ST1) isolated in Sichuan in 1958 used as one of the vaccine strains. Isobaric tags for relative and absolute quantitation (iTRAQ) and parallel reaction monitoring (PRM) were used to compare protein expression differences in the global whole-cell proteome to shed light on the adaptation of current epidemic strains.

Materials And Methods
Bacterial culture and sample preparation Two Leptospira strains from two distinct phylogenetic clusters, namely strain 200502 (ST17) from cluster CC17 and strain 56001 (ST1) from cluster CC1, were selected as representative strains for comparative proteomics. The Leptospira strains were grown in Ellinghausen-McCullough-Johnson-Harris medium (BD Biosciences, San Jose, CA, USA) at 28°C until they reached the log phase. The cell suspension was centrifuged at 10,000 × g for 30 min. Next, the supernatant was removed, and the cell pellet was washed thrice with normal saline, and re-centrifuged at 10,000 × g for 30 min. Thereafter, disruption buffer (8 M urea, 30 mM HEPES, 1 mM PMSF, 2 mM EDTA, and 10 mM DTT) was used to resuspend the cell pellet. Subsequently, whole-cell samples were sonicated at 180 W for 5 min, and the resulting lysate was centrifuged to remove cellular debris. The proteins in the supernatant were quanti ed using the Bradford assay (Bio-Rad Laboratories, Hercules, CA, USA). Three biological replicates were performed for the two strains.
iTRAQ labeling and SCX fractionation Two iTRAQ experiments were performed for the two selected Leptospira strains, with three biological replicates for each strain. For each sample, 100 µg of proteins were digested overnight with 3.3 µg of trypsin (Promega, Madison, WI, USA) at 37°C, followed by freeze-drying. Afterward, the peptides of each sample were reconstituted in 30 µL of 0.5 M TEAB and labeled with the iTRAQ-8plex kit (SCIEX, Framingham, MA, USA) according to the manufacturer's instructions. Samples were labeled with the iTRAQ tags as follows: three replicates of ST1 were labeled with 113, 114, and 115 iTRAQ tags, and three replicates of ST17 were labeled with 116, 119, and 121 iTRAQ tags. After incubation at room temperature for 2 h, the labeled samples were mixed and dried by vacuum centrifugation.

HPLC-MS/MS
The SCX fractions were rst separated by nano-HPLC and then analyzed by tandem mass spectrometry (MS/MS). Brie y, each fraction was re-dissolved in solvent A (2% ACN, 0.1% FA), followed by centrifugation at 20,000 × g for 10 min. Subsequently, using a Dionex ultimate 3000 nano-LC system (Thermo Fisher Scienti c, Waltham, MA, USA), 10 µL of the peptide sample was loaded onto a 2-cm C18 trap column and then gradient eluted by buffer B (98% ACN, 0.1% FA) on a 15-cm analytical C18 column (inner diameter 75 µm) as per the following protocol: ow rate 0.4 µL/min; 5% buffer B for 10 min, a gradient from 5 to 80% buffer B for 38 min, and maintenance at 80% for 7 min. Finally, the system returned to 5% buffer B in 3 min and was maintained at 5% for 7 min.
The LC eluted peptides were then subjected to mass spectroscopy (Q-Exactive MS; Thermo Fisher Scienti c), set in positive ion mode and a data-dependent manner with a full MS scan range from 350-2,000 m/z, full scan resolution of 70,000, MS/MS scan resolution of 17,500, MS/MS scan with a minimum signal threshold of 1E+5, and isolation width of 2 Da. To evaluate mass spectrometric performance of the iTRAQ-labeled samples, two MS/MS acquisition modes and higher collision energy dissociation (HCD) were employed. Furthermore, to optimize the MS/MS acquisition e ciency of HCD, normalized collision energy was systemically examined and stepped by 20%.

Validation Of Differentially Expressed Proteins Using PRM
The changes in protein abundance obtained using the proteomic analysis were con rmed by an LC-MS-based PRM assay. PRM method construction, optimization, and data processing were performed using Skyline software (v3.7.0.11317, downloaded from the MacCoss Laboratory at the University of Washington). Thirteen differentially expressed proteins in the iTRAQ data were selected as candidates for PRM.
Proteins (30 µg) from the whole-cell lysate of the two samples were separately prepared and digested with trypsin following the protocol for tandem mass analysis. The obtained peptides from the two samples were then mixed equally. Next, 2-µg peptide mixtures were introduced into a Q-Exactive MS via a C18 trap column (0.15 × 20 mm; 5 µm; 100 Å) and then via a C18 column (0.75 × 150 mm; 5 µm; 300 Å). The generated raw data were then analyzed using Proteome Discoverer 1.4 (Thermo Fisher Scienti c). The false discovery rate (FDR) was set to 0.01 for the proteins and peptides. Data processing and proteomic analysis were performed using Skyline 3.7 software.

Bioinformatic Analysis
The raw data les generated from the iTRAQ experiments were converted into MGF format les using Proteome Discoverer 1.2 (PD 1.4; Thermo Fisher Scienti c). Mascot software (version 2.3.0; Matrix Science Inc., Boston, MA, USA) was used for protein identi cation by searching against the UniProt-Leptospira_171 database (Number of sequences: 438047), with an FDR of <1%. The key search parameters were set as follows: (I) type of search, MS/MS ion search; charge states of peptides, +2 and +3; (II) the enzyme speci city of trypsin; (III) max missed cleavages, 1; (IV) parent ion mass tolerance, 10 ppm; fragment ion mass tolerance, 0.5 Da; (V) potential variable modi cations, Gln > pyro-Glu (N-term Q); oxidation (M), deamidated (NQ); (VI) xed modi cations, carbamidomethyl (C); iTRAQ8plex (Nterm), iTRAQ8plex (K). To reduce the probability of false peptide identi cation, only peptides with signi cance scores ≥20, FDR <1%, and protein probability >99.0% were accepted. Each con dently identi ed protein included at least one unique peptide. For protein quantitation, Student's t-test was used for statistical analysis, and the relative quantitation of a given protein was reported as the median ratio in Mascot; p < 0.05 was considered statistically signi cant.
Up-and downregulated proteins were de ned as having fold changes (FCs) >1.2 and <0.8, respectively. A two-tailed Student's t-test with FDR correction using the Storey and Tibshirani method was performed with p < 0.05 and q < 0.05 assigned as statistically signi cant. Functional categories were assigned based on KEGG tools [14], and functional analyses for enriched categories were performed using Fisher's exact test.

Results
Comparison of whole-cell proteins of ST17 and ST1 The iTRAQ assay identi ed 2,134 proteins from the 2 strains. Identi ed proteins that were common between the strains were used for quantitative analysis. As a result, 281 proteins were found to be differentially expressed, of which 166 were upregulated (ST17 vs. ST1), and 115 were downregulated (ST17 vs. ST1) (Supplementary Table 1 and Table 2). The ltered results were obtained using ANOVA (p < 0.05, fold change >1.2, or fold change <0.8). The iTRAQ results for the three biological replicates for each strain had good repeatability (R 2 > 0.8) (Supplementary Figure 1).
Of the 166 upregulated proteins (fold change >1.2, p < 0.05), 33 had a fold change >2 in ST17 compared with that in ST1 (Supplementary Table 1). The protein expressions with increased abundance with the top ve changes included lipoproteins, fadD (UniProt ID Q72RV8), 50S ribosomal protein L17, and two other uncharacterized proteins (UniProt ID M3HFM4 and M6HIJ0) in ST17. In addition, the fold increases were more than eight (Supplementary Table 1). Of the 115 downregulated proteins (fold change <0.8, p < 0.05), 26 had a fold change <0.5 in ST17 compared with that in ST1, and the top ve changes included long-chain fatty acid-CoA ligase, acetyltransferase component of the pyruvate dehydrogenase complex, transketolase, glycine dehydrogenase, and uncharacterized protein (UniProt ID A0A0F6HXF1; Supplementary Table 2).

Functional Roles Of Proteins With Differential Expression
For the functional categories, all 281 differentially expressed proteins were analyzed for functional annotations based on the KEGG database. As a result, 129 of the 281 proteins were annotated successfully, although the functions of most proteins were unknown. The annotation results of 79 upregulated and 50 downregulated proteins are shown in Figure 1. Carbohydrate metabolism, genetic information processing and signaling, and cellular processing constituted the highest proportion of total annotated results (50.6%) of upregulated proteins (Supplementary Table 1). In addition, it was shown that several outer membrane proteins (Omps), lipoproteins, and other known virulence factors (such as BrkB) were found to be upregulated in ST17 (Supplementary Table 2). Unlike with upregulated proteins, environmental information processing and energy metabolism-related functions were reported in downregulated proteins, while other metabolism-related proteins were fewer, for instance, 19 vs. 6 for carbohydrate metabolism, 8 vs. 3 for amino acid metabolism in ST17 and ST1, respectively (Figure 1 and Supplementary Table 2).
To further understand the differentially expressed proteins, subcellular protein location and secretion type were predicted bioinformatically. It was shown that 57.2% of upregulated proteins were located in the cytoplasmic membrane while 21.1% were in the cytoplasmic space. Furthermore, 5.4%, 3.0%, and 2.4% of upregulated proteins were localized in the outer membrane and extracellular and periplasmic spaces, respectively; the location of 10.8% of the proteins was unknown (Supplementary Table 1). Regarding secretion pathways of upregulated proteins, 27 proteins (16.3%) were predicted to be secreted by the classical pathway, while 15 proteins (9.0%) were predicted to be nonclassically secreted, and most proteins (74.7%) were assigned to an unde ned secretion type (Supplementary Table 1). Unlike upregulated proteins, most downregulated proteins (76.5%) were located in the cytoplasmic space, with none found in the periplasmic space. Additionally, 17.3%, 3.4%, and 1.7% of proteins were found in the cytoplasmic membrane, extracellular space, and outer membrane, respectively (Supplementary Table 2). Similar to upregulated proteins, most downregulated proteins (68.7%) were predicted to have an unde ned type of secretion, whereas 17.4% and 13.9% of proteins were classically and non-classically secreted, respectively (Supplementary Table 2).
PRM con rmation of selected proteins PRM assays, as a con rmatory technique, were designed to quantitate proteins that were determined to be differentially expressed by iTRAQ between the two strains. As described in the Materials and Methods section, 13 differentially expressed proteins were selected as candidates ( Figure 2 and Table 1). PRM results showed that 10 of the 13 proteins, including OmpL1, LipL71, peptidase M75, FAD-binding protein, signal peptide peptidase (SppA), agellin, bifunctional purine biosynthesis protein (PurH), putative lipoprotein, and one uncharacterized protein, had a consistent fold change trend in the iTRAQ assay. Moreover, 3 of the 13 proteins, including cysteine synthase (cysK), sigma factor regulatory protein (FecR/PupR), and transcriptional regulator protein (TetR family), had an inconsistent fold change trend in the iTRAQ assay (Table 1). 57.11(0.020) a: No signal-peptide was predicted and the SecretomeP analysis was negative b: signal-peptide was identi ed in at least two software c: SecretomeP analysis was positive and one or none signal-peptide was identi ed.

Discussion
Leptospirosis incidence has signi cantly decreased in the past 20 years; regardless, the disease is still considered an important reportable zoonotic disease in China [3]. Several studies demonstrated that serogroup Icterohaemorrhagiae is the most predominant in China, being responsible for over 60% of leptospirosis cases, although the predominant serogroups or STs differ geographically by country and region [10]. Recently, 17 different STs were identi ed in 120 Chinese Leptospira serogroup Icterohaemorrhagiae strains collected from 1958 to 2008, including 69 ST1, 18 ST17, 18 ST128, 9 ST143, and 2 ST209 strains, which differed from those isolated in other countries, such as Argentina, Russia, and Brazil where ST17 is predominant [11]. It is speculated that these predominant isolates may have adaptive selective advantages in the environment or in maintenance hosts.
In the present study, it was shown that at the proteomic level, there were a few key proteins that differed between ST1 and ST17 among the serogroup Icterohaemorrhagiae strains from different periods, though the expression of most proteins showed no difference. There were nine outer membrane proteins whose expression increased in ST17, including the known proteins OmpL1 [19.20], lipL41 [21,22], and lipL71 [23,24]. OmpL1, a 31-kDa leptospiral transmembrane protein, was found to be upregulated with a 5.95-fold increase in ST17. Previous studies demonstrated that recombinant OmpL1 induced partial immunoprotective capacity in an animal model [14]. Additionally, OmpL1 was found to be synergistically immunoprotective in combination with LipL41 in a Golden Syrian hamster model challenged with pathogenic Leptospira, indicating that OmpL1 and LipL41 are important determinants of immunoprotection [25]. The expression differences of immunogenic proteins between the vaccine strain and the circulating isolates may imply the need to select new vaccine strains. Therefore, these data can provide critical insights for developing new whole-cell and recombinant leptospirosis vaccines.
On the other hand, bacterial OMPs, as the rst points of interaction with a host, play crucial roles in attaching to host cells by acting as receptors for various host molecules, functioning as porins, and/or acting as bactericidal antibody targets. These properties contribute to bacterial pathogenesis by helping bacteria evade the immune response or adhere to tissues [26]. OmpL1, a surface-exposed protein, exhibits typical receptor-ligand interaction by binding laminin and plasma bronectin. Furthermore, the interaction of OmpL1 with plasminogen can produce plasmin, facilitating host cell membrane degradation by bacteria [20]. It has been suggested that OmpL1 may promote the attachment of leptospires to mammalian hosts by helping the bacteria disseminate during the infection process. These differences in OmpL1 expression may contribute to tness differences between the two strains. Consistent with this assumption, LipL71, also known as LruA, a lipoprotein encoded by the LIC_11003 gene containing a LysM domain between residues 401 and 461 and associated with peptidoglycan binding in bacterial expression, was also upregulated in ST17 [23]. It was found that LruA share immunorelevant epitopes with eye proteins, suggesting that cross-reactive antibody interactions with eye antigens may play an important role in Leptospira-associated recurrent uveitis [27]. Furthermore, it was demonstrated that the 232 amino acid deletion at the C terminus of LipL71 (covering the LysM domain) resulted in attenuation of leptospiral virulence by modulating cellular interactions with serum protein ApoA-I, suggesting that LipL71 is a surface-exposed virulence factor that is closely associated with leptospiral pathogenesis [24]. To advance the understanding of leptospiral pathogenesis, further genetic manipulation should be performed in future studies to con rm that the differentially expressed proteins identi ed in this study are key contributors to the tness difference between the two clusters.
It is generally accepted that transporter proteins may be closely associated with the metabolic diversity of bacterial pathogens[28], and L. interrogans has over 250 transporter proteins [29]. We found that four transporter proteins were upregulated while two transporters were downregulated in ST17. This differential expression of various transporters suggests that the two strains differed metabolically, with the likelihood of ST17 being more metabolically e cient than ST1. Furthermore, several carbohydrate and amino acid metabolism-related proteins were highly expressed in ST17, implying a higher ability to acquire essential nutrients, providing further evidence that ST17 was metabolically more e cient. This re ects the metabolic diversity and potential of the pathogens to adapt to different environments. We suggest that these changes might be common across current circulating ST17 strains globally, contributing to their expansion.
As a targeted proteomics technology based on high-resolution, high-precision mass spectrometry, RPM can absolutely quantify target proteins and peptides [30]. This quantitative technique has been demonstrated to be better than western blotting, which is semiquantitative, less sensitive, and requires antibodies that may not be available [31,32]. In the present study, signi cant differences in iTRAQ results were con rmed using MRM RPM. There was a strong correlation between RPM and iTRAQ results, although 3 out of 13 proteins exhibited inconsistent fold change trends. The minor lack of conformity may be attributed to the different working principles of the two methods. RPM targets speci c peptides and transitions, which may be missed during iTRAQ as in shotgun proteomics, where more peptides are eluted than can be detected at once [32,33].

Conclusions
In conclusion, a total of 281 differentially expressed proteins were identi ed between ST1 and ST17 in serogroup Icterohaemorrhagiae strains from different periods using comparative proteomics technology. Expression up-regulation of some important proteins, including several known immunogenic and/or virulence-related OMPs and lipoproteins, were found in the most prevalent circulating ST17 strain, providing critical insights for the development of whole-cell and recombinant leptospirosis vaccines. Furthermore, the differential metabolism-related proteins identi ed may be key contributors to the tness difference between the two ST clusters.

Funding
This work was supported by the National Key R&D Program of China (No. 2018YFC1603900) and The National Natural Science Funds, China (No. 81471968). Associated heat map between iTRAQ and PRM quantitation. Proteins labeled with pentacles indicated that results between the two assays were inconsistent

Supplementary Files
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