extfieldsofstudy: Biology Medicine

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Effect of fetal bovine serum in culture media on MS analysis of mesenchymal stromal cells secretome

Graphical abstract

Secretome Fetal bovine serum Tandem mass spectrometry Mesenchymal stem cells A B S T R A C T
The analysis of mesenchymal stromal cells secretome is fundamental to identify key players of processes involving these cells. Truly secreted proteins may be difficult to detect in MS based analysis of conditioned media (CM) due to proteins supplemented with fetal bovine serum (FBS). We compared different growth conditions to determine the effect of varying FBS concentration on the number and quantity of truly secreted human proteins vs contaminating bovine proteins. The results suggest that to minimize interference cells should be grown in presence of FBS until confluence and transferred into a serum-free medium prior to secretome collection.
2016 The Authors. Published by Elsevier B.V. on behalf of European Proteomics Association (EuPA). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).
Postnatal stem cells can be obtained from different somatic tissues and have the capacity to self-renew and differentiate into multiple cell types [1]. Mesenchymal stem cells (MSCs) can also modify the immune response and secrete paracrine mediators, reducing inflammation and accelerating tissue regeneration by activation of resident stem cells and mobilization of circulating systemic stem cells through chemotactic signalling [2]. Since the secretome plays a direct role in the biological activities of MSCs, the qualitative and quantitative analysis of the protein components of MSCs secretome is a fundamental step in order to identify key players in the control and regulation of the many biological processes influenced by these cells.
Only a few studies have characterized the cellular secretome in vivo [3,4] because of the inherent difficulties. A commonly used approach is the analysis of media conditioned by cells in culture (CM) [5][6][7][8]. This model assumes that cells grown in vitro and stimulated using specific factors known to be which cells are exposed under certain conditions in vivo present a secretion phenotype similar to the one in vivo. The obvious advantage of cells in culture is the possibility to study variations of the secretome induced by specific events in a simplified environment and translate these findings for the preparation of material designed for therapeutic applications. Despite the complexity reduction and the experimental advantages offered by in vitro model systems, secretome profiling based on CM analysis presents serious difficulties, such as the low concentration at which the proteins are secreted and the presence of high abundant supplemented proteins fromserum (often fetal bovine serum, FBS) in the CM [8,9] which often mask the lower abundant proteins secreted by cells, concealing their identification by mass spectrometry [10]. Moreover, in a typical shotgun LC-MS/MS experiment, FBS contaminants are sometimes difficult to discriminate from the human proteins truly secreted by cells, because of shared peptide sequences between species [11].
However, since serum deprivation might slow down and even stop cell proliferation [12,13] increasing cell death [14], growth media should be supplemented with FBS at least for a defined time frame, in particular until MSCs reached the confluence, prior to secretome collection.
In this study, we compared three different growth conditions to determine the effect of varying FBS concentration in the CM of human bone marrow MSCs (BM-MSC) on the number and quantity of truly secreted human proteins vs contaminating bovine proteins. Ethical Approval for marrow aspiration and stromal cell isolation was obtained from Galway University Hospital Clinical Research Ethics Committees (GUH-CREC).
For this purpose isolated BM-MSC were seeded in tissue culture treated flasks in DMEM 20% FBS and incubated at 37 C until confluence. After reaching 70-80% confluence, the adherent cells were trypsinized, harvested and expanded in larger flasks. Growth medium was substituted with DMEM low glucose supplemented with 25 ng/mL hIL1b, 20 ng/mL hIL6 and 25 ng/mL hTNFa and 0%, 5% or 10% FBS for 24 h. Cells were washed 3 times with DMEM without serum, incubated for 18 h and the conditioned medium was collected and concentrated using Centricon 10 (Millipore) centrifuge filter unit.
Fifty micrograms of total proteins from each experiment were reduced with DTT, alkylated with iodoacetamide, digested with trypsin sequence grade for 16 h at 37 C using a protein:trypsin ratio of 50:1 (w/w) and desalted using ZipTip (Millipore) as detailed in [15]. NanoLC-ESI-MS/MS analysis was performed on a LTQ Orbitrap Velos (Thermo Fisher Scientific) equipped with a Dionex UltiMate 3000HPLC system. Raw data were analyzed using MaxQuant software (version 1.3.0.5) as detailed in [15,16]. The acquired MS/MS spectra were analyzed by the Andromeda search engine, against the human Uniprot sequence database (release 2013_05) and the bovine UniProt sequence database (release 2013_05). Comparative analyses were performed using the Perseus software (version 1.4.0.6) (http://coxdocs.org/doku.php?id=perseus:start). Table 1 summarizes the main results obtained from each hMSC growth condition: 0%, 5% and 10% of FBS. Whereas the total number of identified bovine secreted proteins is approximately the same in each sample, the total number of identified human secreted proteins is about twice when hMSCs were grown in 0% and 5% FBS culture medium compared to cells grown in 10% FBS culture medium. This positive result is due to a very significant decrease in MS signals due to bovine, i. e. contaminating, proteins, as shown in Table 1. Taking the sum of ion intensities of human or bovine proteins as an approximate estimation of protein quantities deriving from the two organisms, it can be observed that 0% FBS maximizes the signals due to human proteins, allowing detection of the less abundant ones. The lists of proteins exclusively expressed in the three different growth conditions are provided as supplementary material in Table S1 (0% vs 5% FBS), S2 (5% vs 10% FBS), and S3 (0% vs 10% FBS). As shown in Fig. 1, significant overlap of proteins identified in the different conditions can be observed; in particular most proteins detected in 10% FBS are also found under the other two conditions.
To get a more detailed overview of the effect of varying FBS concentration, we compared the results of a gene ontology biological process (GOBP) analysis on the proteins identified in the three conditions ( Figure S1). Since a very important parameter to define whether a secretome analysis is reliable is the percentage of "truly" secreted out of the total proteins identified, two very popular prediction programs, SignalP [17] and SecretomeP [18], were used to implement the secretion category of the GOBP analysis. As expected, more than 70% of human identified proteins are predicted as "secreted" under all conditions: 74% (215 proteins) in 0% FBS, 74% (213 proteins) in 5% FBS and 72% (108 proteins) in 10% FBS. In accordance, Figure S1 show that overall that the absence of FBS in the CM does not lead to qualitative changes in the biological processes related to secretome components. Interestingly, cellular component disassembly, death and cell death are little represented biological processes under all conditions, suggesting that the 0% FBS condition does not promote precesses leading to a higher number of lysing cells. Finally, although the function of individual proteins identified is out of the scope of the present communication, it should be noted that several proteins belong to GOBP categories related to response to stimulus.
In conclusion, this analysis allows to define an optimized protocol to collect the secretome of human BM-MSC in order to detect the differential expression of secreted proteins induced by exposing cells to specific stimulation conditions in future studies.


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A systematic, large-scale comparison of transcription factor binding site models

The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified “real” in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. While the area-under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM ( http:/mutationtaster.charite.de/ePOSSUM/ ) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites.

Background
Transcription factors (TFs) are major players in the regulation of gene activity. They bind to DNA target sequences known as transcription factor binding sites (TFBSs) in order to up-or down-regulate transcriptional activity. As DNA binding is pivotal to correct TF function, mutations in TFBSs can lead to genetic disease [1,2].
However, despite the rapid growth in the number of mutations known to cause Mendelian disorders, the number of confirmed mutations in regulatory sequences is still low, presumably due to difficulties in experimentally verifying their functional relevance as the cause of a given disease.
With each deep sequencing run a large number of DNA variants are found, many of which may be considered as potentially causing Mendelian disorders, even after bioinformatic filtering. Hence the main challenge is currently not the generation, but the interpretation of the data. While considerable progress has been made at the in silico analysis of alterations in the protein coding sequences (e.g. MutationTaster [3], SIFT [4], PolyPhen-2 [5]), these prediction tools address the role of variants within potential regulatory sequences only indirectly, e.g. via their evolutionary conservation, or the simple fact that a variant occurred somewhere within a confirmed regulatory element. We thus set out to examine and compare the relevance of methods for computational TFBS recognition as a means to assess the diseasecausing potential of genetic variants.
Currently, the state-of-the art method for functionally representing TFBSs is via transcription factor binding models that are described by matrices, such as positionspecific scoring matrices (PSSMs), also called position weight matrices (PWMs). These PSSMs are normalised representations of the position-specific log-likelihoods of a nucleotide's probability to occur at each location in an observed sequence [6]. PSSMs can be used to computationally detect putative TFBSs in regulatory regions by establishing a match score, which determines how well a given sequence matches with a TF binding model.
A manually curated census in the year 2009 counted 1391 TFs in humans [7]. This number has grown since then-estimates for the total number of human TFs currently range between 2000 and 3000 [7,8]. However, only a fraction of these factors have been studied intensely enough to generate reliable binding models; the ENCODE (Encyclopaedia of DNA Elements) project, for example, offers one of the largest collections of experimentally verified binding instances, but only covers 161 different TFs [9].
Moreover, various other repositories of TF binding models exist that have been obtained by different methods, but still fall short to represent the predicted TF landscape in humans. The largest of these repositories, TRANSFAC [10], is not freely available and has therefore not been included into this survey. The human Protein-DNA Interactome (hPDI) [11] contains matrices for 493 human TFs generated through Protein-Binding Microarrays (PBMs), whereas a recent publication [12] determined over 200 matrices for 151 human TFs via an HT-SELEX experiment. HT-SELEX enables the identification of DNA target strands through a large library of artificially generated oligonucleotides, which are presented to a target protein. Bound sequences are amplified by PCR, followed by several rounds of selection processes to determine the best-bound sequences. It is not surprising that binding models derived from different experimental methods can show highly different success rates in modelling TF-DNA binding. However, for a long time it was impossible to compare the quality of binding models that had been obtained by various methods due to the lack of sufficient experimental data.
Therefore, only recently a direct comparison between TF models derived from PBM and HT-SELEXexperiments has been published [13]. This study found models generated through both experimental strategies to be quite similar for in vitro binding, whereas for in vivo prediction HT-SELEX-derived models achieved better results.
Here we present a larger study in which we set out to compare a total of 179 PSSMs linked to 82 different TFs that derived from the following three sources: HT-SELEX, PBM, and the manually curated binding models provided by JASPAR [14]. Almost all of the 58 JASPAR matrices (representing 56 TFs) used in our study resulted from ChIP-seq experiments, only two, aimed at NFIC and RELA, were generated by HT-SELEX experiments. We tested all models for their capability to recognise ChIP-seq confirmed functional ('in vivo') TFBSs from the ENCODE project [15]. Due to the presence of several TFs in more than one binding model source, we were able to directly compare matrices linked to 26 different TFs from JASPAR and HT-SELEX, thereby enabling a quality assessment of binding models obtained through different experimental methods. For this study, we created two test sets, one comprising all suitable TFBSs from ENCODE and another one which includes only those TFBSs with a high binding score ('high-confidence set'). We used the same number of lengthmatched exonic sequences as a TFBS-depleted control set.
This study is to our knowledge the largest comparison of TF binding models, testing 179 binding models (PSSMs) on over 2 x 2,000,000 target sequences in total. Hence, our study provides insight into the current quality of computational TFBS predictions and the findings generated in this study may help to evaluate the feasibility of whole-genome TFBS prediction studies.

Binding predictions
We tested the PSSMs mentioned above and used ChIPseq derived sequences binding to TFs as positive controls. Results were assessed with ROC analysis (see Methods for details).
The various binding models from the multiple sources yielded different results in many cases: While only 3 of the 19 PBM-derived models from hPDI (16 %) reached an AUC score of ≥0.7, this was the case for 46 % of the HT-SELEX and 60 % of the JASPAR-models. The average AUC values generated by the different binding model sources were highly divergent, ranging from 0.53 (hPDI) to 0.72 (JASPAR).
When tested on the 'high-confidence' dataset, 4 out of 15 models (26.6 %) from hPDI yielded AUC scores of ≥0.7, which resulted in an average AUC score of 0.57. The HT-SELEX-models reached AUC values ≥0.7 in 70 % of the cases (average AUC of all PSSMs: 0.76), whereas the JASPAR-matrices generated an average AUC score of 0.83. An overview of these findings is depicted in Fig. 1.
We were able to directly compare the prediction quality of models for 28 different TFs that were represented in both the JASPAR and the HT-SELEX data (26 for the high confidence test set). We found that in general, the manually curated matrices from JASPAR enabled a slightly better distinction between positive and negative sequences (average AUC 0.74 versus 0.70). In the 'highconfidence' data set, these values increased for both data model sources: The HT-SELEX models generated an average AUC of 0.80, whereas for JASPAR this value was 0.84 ( Figs. 1a and 2).
These findings can help to estimate the utility of TFBS models from different sources, enabling researchers to better circumvent the high false-positive rate, a problem which is well known for in silico TF binding analyses [16], and thus to make the most of the available data. In general, we found manually curated models provided by JASPAR and HT-SELEX-derived matrices to be much more successful in recognising in vivo TFBSs than PBM derived models.
Previously, the success of TF binding prediction has been found to be similar for the majority of matrices, with degenerate matrices yielding the most accurate predictions [17]. Hence researchers currently often use TF binding models from various sources indiscriminately. The notion that TF binding models obtained through different experimental methods can be variable has just recently entered the scientific discourse in a novel publication [13]. There, the authors compared PBM-and HT-SELEX-derived models and found both models to be reliable with a slight advantage of HT-SELEX models in the prediction of in vivo TFBSs. Our study on a larger test set (up to several thousand binding events per TF with direct comparison of models from different sources for a subset of the tested TFs) showed JASPAR to be the most reliable source for TFBS matrices in this data set. To check if the higher accuracy of JASPAR might be the result of an overfitting of the JASPAR models to the ENCODE data, we manually checked for an overlap between the tested matrices and the ENCODE data set. For each PSSM, we studied the accompanying publication and found that this was not the case for any of the binding models included in our study. Hence we can safely assume that the current JASPAR models are indeed the most successful ones to recognise in vivo TFBSs.
In this study, we decided to use exonic sequences as a negative test set. Because the 5' regions of genes occasionally contain functional binding sites [18,19], we decided to categorically exclude the first exon of each transcript from our analyses. Thus, the percentage of functional TFBSs in the negative test set should be sufficiently decreased in order to allow computational predictions. We preferred this approach to alternative analyses, such as the usage of artificially generated random DNA sequences without TFBSs, as they might be very different from naturally occurring sequences and are also likely to increase error rates [20]. Furthermore, the usage of random exonic sequences as a negative set closely mimics the real-life research situation, therefore allowing an important insight into the limitations of current in silico TFBS analysis methods.
We found that the usage of only high-confidence EN-CODE data leads to an increased reliability in the computerised recognition of TFBSs. However, this filtering step also introduces a potential drawback: Strong TF binding does not necessarily implicate strong TF function, as has been shown for D. melanogaster [21], where low-affinity binding sites can be of great importance for normal gene activation. Moreover, a researcher looking for a functional binding site in silico does not necessarily have any previous knowledge on the binding strength. Therefore, the decision to admit only high-confidence data into analyseswhich is common practice in TF binding research [13,17,22]-in fact excludes a large amount of relevant information and should therefore be taken with care.

Conservation analyses
In a real-life research situation, TFBS predictions are usually supplemented by additional analyses such as the determination of sequence conservation. We therefore further tested whether the ENCODE TFBSs (positive set) show a higher degree of conservation than the Fig. 2 Direct comparison of binding models generated by different methods. Depicted are AUC scores for TFs stored in both JASPAR (manually collected curated models) and HT-SELEX. AUC scores were generated using ROCR. If multiple binding models were available for one TF, we depict the average AUC value genetic background. In detail, we measured phyloP [23] and phastCons [24] scores for each position of the EN-CODE TFBSs and of negative test cases (length-matched random sequences from chromosomes 1 and 2). For each TF, we then calculated the average scores of the highest conservation as well as of the average conservation score reported for each sequence. As we did not know where exactly in the ENCODE sequence the actual TFBS was located, we chose to focus on the highest conservation scores, assuming that functional TFBSs would show a high degree of conservation. However, we found that, while there was a higher degree of conservation for the ENCODE sequences, the variability in the tested sequences was very high. Moreover, we did not find a link between strong TF binding and sequence conservation because the mean maximum phyloP and phastCons scores for the high-confidence test set were not significantly higher than for all ENCODE sequences. We hence conclude that, while this may sometimes be the case, a functional binding site does not necessarily have to be highly conserved. As a representative example, Fig. 3 shows example images of conservation readings for ZBTB33 and BCL11A.
Our findings indicate that while there seems to be a certain degree of increased conservation for ChIP-seq verified TFBSs in comparison to random genetic sequences (Fig. 3), the variability between individual sites is too high to draw any reliable conclusions. These results support previous findings, which suggest that functional TFBSs can, but do not have to be evolutionarily conserved with regard to their primary nucleotide sequence [25][26][27]. More precisely, some researchers argue that TFBSs may fluctuate quite rapidly between species. For instance, it has been found in a comparative genomics study that the likelihood of a TFBS to be conserved between S. cerevisiae and its two closest relatives (S. paradoxus and S. mikatae) lies below 5 % for a majority of the sites [26]. In addition, rapid evolution of combinatorial transcription networks was found for the transcriptional regulator MCM1 in closely related fungi species [28]  introducing local point mutations showed TFBSs and combinations of binding sites to evolve quickly [29]. Considering the fact that TFBSs are known to be relatively variable, even within the same species, it would be surprising if all functional binding sites were conserved across larger evolutionary distances [27,30,31]. It has also been shown in comparative studies between various species that the functionality of TFBSs can still be preserved despite underlying sequence changes [32,33]. The three-dimensional structure of the DNA at a TFBS, including the histones, is likely to play an important role for TF binding, a notion which is slowly being acknowledged for the analysis of TFBSs [34]. As such three-dimensional structures can be well conserved while the underlying linear sequence may evolve rapidly, sequence conservation scores might not be of major importance for the assessment of TFBSs. In our study, we found that the degree of variation between individual TFBSs was too high to infer TFBSs conservation in general.
Hence, measurements such as genomic location or three-dimensional conservation might be better suited for the assessment of the validity of a TFBS.

Regulatory SNPs (rSNPs)
We compiled a set of 52 rSNPs known to directly impact TF binding or gene expression (included as Additional file 1). rSNPs are single-nucleotide polymorphisms occurring in regulatory regions such as promoters or enhancers. They are likely to be of functional significance as they do affect transcription initiation, elongation, and translational characteristics of mRNA but are more difficult to study than alterations in coding regions and are hence underrepresented in the literature [35][36][37]. We only included alterations in this test set which have been shown to directly interfere with a TFBS's function in in vitro or in vivo experiments. In this test set, we found differences between wild-type and mutant variants with respect to the evaluated maximum binding scores in 76 % of all observations, but they rarely exceeded 20 %. For a subset of the rSNPs, which linked to 15 different TFs (represented by 58 PSSMs from JASPAR, hPDI, and HT-SELEX), we were able to directly compare the computational predictions to the experimental findings. If solely considering maximum binding score changes, we found agreement between computational and experimental results in less than 50 % (48.1 %) of the tested matrices. However, when analysing the data with ePOSSUM (see below), we obtained a correct prediction in 62 % of the cases. Interestingly, the different binding models from the various sources again yielded quite divergent results, thus confirming strong variability in the quality of the tested matrices (see Additional file 1). We are aware that the rSNP test set used in this study was not large enough to provide comprehensive insight. This is due to the fact that experimental data on rSNPs in TFBSs are not readily available. Hence, we decided to make the best of the available data and to provide an initial glimpse into the reliability of the state-of-the-art methods for TFBS prediction.

ePOSSUM
Our study demonstrates that many of the existing PSSMs offer only limited reliability, while others do indeed allow reasonable predictions. In order to make our findings readily available to the scientific community, we created software called ePOSSUM that predicts the effect of genetic variation on TF binding using the matrices included in our study. It also includes a measure of significance of the assessments to indicate how reliable a prediction by a certain PSSM would be.
ePOSSUM is a web-based application that can be freely accessed at http://mutationtaster.charite.de/ePOS-SUM/. Users can either enter genetic variants in the common VCF format or wild-type sequences along with the variant sequences. In the first case, the position of the variant is known and ePOSSUM scans the ENCODE ChIP-seq data used in our study for known TFBSs around this position. The existence of TFBSs at the position under study is included in the output. In total, ePOSSUM offers predictions for 81 TFs which are based on 171 different PSSMs. To speed up analysis, users can choose which TFs to include into the search for binding sites. If they submit a genomic position, they can limit the search to those TFs that are known to bind at this position.
Unlike similar applications such as motifbreakR [38], ePOSSUM does not merely subject sequences to different PSSMs, but uses their binding scores as input for a Bayes classifier. More precisely, this classifier uses the quotient of the maximum binding scores calculated for wild-type and variant sequence to determine whether the genetic alteration leads to the (predicted) gain or loss of a TFBS. As most of these quotients do not show a normal distribution, we use the R module klaR [39] for the classifier, which considers the kernel-density, i.e. the real distribution of values, to generate predictions.
Due to the poor performance of many PSSMs in discriminating real TFBSs from exonic sequences as indicated by similar maximum binding scores for both, the Bayes probability for both outcomes (TF binding versus no TF binding) is often far from 100 %. We therefore include the negative or positive predictive value (NPV/ PPV) for each matrix for the given Bayes probability as a measure of the reliability of the classifier's prediction.
This value is also used to colour-code the likelihood of increased/new or decreased/lost TF binding. Darker colours represent more likely changes in TF binding. ePOS-SUM uses all available PSSMs for a TF to generate a final assessment-here, only PPVs/NPVs of 70 % or above are considered. The assessment also includes whether or not a binding site for the TF was reported by ENCODE at the respective genomic location.
Different Bayes classifiers were trained for each PSSM with the quotients of all possible pairs of positive versus negative cases for the respective TF using all available sequences from our ENCODE high-confidence set as positive and exonic sequences as negative cases. The number of pairs was deliberately limited to 1,000,000 per matrix, even if more pairs were possible. ePOSSUM is limited to human TFs and, if genomic positions were used, to genome version GRCh37. A weakness lies in the recognition of known TFBSs-as each TFBS positive ChIP-seq snippet from ENCODE comprises several hundred bases, we do not know whether or not the "real" TFBS is truly located within the fragment screened in the analysis.

Conclusions
The assessment of variation in regulatory sequences remains a substantial challenge for the research community. While in previous decades genetic analyses focused on protein-coding regions, due to the availability of deep sequencing the search for regulatory mutations has meanwhile become a research focus. The properties of TF binding have been investigated for a long time and therefore offer a myriad of data for computational analyses. However, the utility of TF binding models for large-scale TFBS recognition has not been extensively investigated yet.
Therefore, this study is an attempt at comparing the accuracy of TF matrices obtained by various experimental methods in predicting functional TFBSs on a large scale. Thus, it enables an analysis of the quality and relevance of current TF binding prediction data.
Problems in predicting TFBSs in silico include high false-positive rates [16] high variability [30,40], and insufficient knowledge of the exact in vivo binding sites [17,41]. Current TF binding models are usually based on mere one-dimensional sequence parameters, which poses a major limitation.
To tackle these problems, researchers have to wisely choose data sources as well as TFBS predictors. Taken together, our analysis and the newly created and free-touse software ePOSSUM provide previously unknown quality measures for computational TFBS predictions thus enabling researchers to extract and use the most meaningful of the available data.

TF binding models
TF binding matrices generated via three different experimental methodologies were obtained from the R package MotifDb [42]. This tool contains a large and up-to-date collection of freely available TF binding models. We used human PSSMs from some of the largest and most frequently used 'open source' TFBS data sources: hPDI (19 matrices), JASPAR (58 matrices linked with 56 different transcription factors), and HT-SELEX studies (102 matrices linked with 47 different factors). For hPDI and JASPAR, usually one matrix was available per TF, whereas the HT-SELEX data reported up to six variants per TFs. The tested PSSMs were highly variable, ranging from approximately 5 to 19 bp length, with hPDImatrices being generally shorter than models obtained from the other two sources. In this study, in order to obtain comparable results, we only evaluated monomeric binding models, despite the fact that the latest issue of JASPAR also contains a number of homodimeric models. An overview of the binding models can be found in Fig. 4 and in the Additional file 2. The positive test set consisted of ChIP-seq confirmed TF binding events, which were obtained from the EN-CODE project [9] (March 2012 Freeze), as provided by the UCSC [43]. This data includes TF binding instances found in ChIP-seq experiments that had been performed on various human cell lines. For each binding event, the genomic location is reported together with a binding score indicating the strength of the protein-DNA interaction.

High-confidence positive test set
In the first step of the experiment, all reported ChIP-seq instances were incorporated into the workflow. In a second approach, only sequences reaching at least 80 % of the maximum possible binding score published by EN-CODE were included into a 'high-confidence' test set. Of these cases, we only tested TFs for which at least 100 binding instances were reported by ENCODE to reach this threshold. Hence, 15, 44, and 55 TFs remained for hPDI, HT-SELEX and JASPAR, respectively.

TFBS-depleted DNA (negative test set)
For the negative test set, we used exonic sequences (GRCh37) which we obtained via Ensembl-Biomart [44]. For each sequence of the positive test set, we randomly selected an exonic sequence of equal or greater length to the corresponding TFBS sequence; in case of longer exonic sequences, these were shortened randomly to match the TFBS sequence. We routinely omitted the first exon of each transcript in order to decrease the chance of erroneously including TFBSs located downstream of the transcription start site [18,19].

Binding predictions
We applied each PSSM included in this study to the respective ENCODE sequences and their length-matched exonic negative controls. In total, we tested 179 models that were linked with 82 different TFs on over 4,000,000 positive and negative sequences.
Binding of a TF to a target sequence was determined using R and the Biostrings [45] function matchPWM (see Implementation). MatchPWM is a simple matching algorithm, which takes a DNA target sequence and a PWM (PSSM) of interest as inputs and computationally determines a match score. Each PWM has a theoretical maximum PWM score, which can be obtained by summing up the strongest weights. For each position of the target sequence, matchPWM compares the match score with the maximum score of the model and reports each hit above a user-defined threshold, which we set to 20 % in order to also detect 'weak' binding site predictions. For each of the positive and negative test set entries, we then conducted scans of both the forward and the reverse strand and determined the maximum score found within the respective pair of forward/reverse sequences. For each matched pair we thus obtained two scores, one for the true TFBS case and one for its control sequence.
The binding models in MotifDb are stored in position frequency matrices, where each column sums up to 1. MatchPWM, however, expects a position weight matrix or a position count matrix with column sums different to 1. To work around this problem, we multiplied each matrix field by the scaling factor of 100 to obtain matrices of the desired scale. As the sequences in the positive test set have been experimentally shown by the EN-CODE project to contain functional TFBSs, they were expected to yield a significantly higher ratio of high match scores than their negative counterparts.
We then applied receiver operating characteristic (ROC) analyses as provided by the R package ROCR [46] to test the discriminative power of score assignments.

Conservation analyses
Conservation scores for the three different groups of test sequences (ENCODE sequences, ENCODE highconfidence set, random length-matched control sequences) were generated using phyloP [23] and phastCons [24]. For these analyses, we obtained conservation scoring files for multiple alignments of 45 vertebrate genomes to the human genome ('46 way') from the UCSC PHAST package [47]. As exonic sequences are expected to be highly conserved, the negative test set for TF binding (exonic sequences, exon 1 omitted) could not be used for this analysis. Therefore, we generated a data set of random sequences by picking random genomic positions on chromosomes 1 and 2 and length-matching the sequences to ENCODE TFBS snippets.

Regulatory SNPs (rSNPs)
As a proof of concept, we tested some of the available binding models on a small test set of 52 experimentally verified regulatory single nucleotide polymorphisms (rSNPs) that were reported in the literature. For these rSNPs the effect of the alteration on TF binding and/or gene regulation had been determined experimentally in wet-lab experiments. We collected relevant rSNP positions through an extensive literature research and then tested the corresponding binding models on a DNA sequence snippet spanning 20 bp 3' and 5' of the respective rSNP. Repositories or collections of verified alterations in TFBSs were found in a limited number of publications [40,[48][49][50], while other data was compiled manually from the literature. A summary of the rSNP test set listing the individual publications for each of the tested variants can be found in the Additional file 1.


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“Quinone Millipedes” Reconsidered: Evidence for a Mosaic-Like Taxonomic Distribution of Phenol-Based Secretions across the Julidae

The defensive chemistry of juliformian millipedes is characterized mainly by benzoquinones (”quinone millipedes”), whereas the secretions of the putative close outgroup Callipodida are considered to be exclusively phenolic. We conducted a chemical screening of julid secretions for phenolic content. Most species from tribes Cylindroiulini (15 species examined), Brachyiulini (5 species examined), Leptoiulini (15 species examined), Uncigerini (2 species examined), Pachyiulini (3 species examined), and Ommatoiulini (2 species examined) had non-phenolic, in most cases exclusively benzoquinonic secretions. In contrast, tribes Cylindroiulini, Brachyiulini, and Leptoiulini also contained representatives with predominantly phenol-based exudates. In detail, p-cresol was a major compound in the secretions of the cylindroiulines Styrioiulus pelidnus and S. styricus (p-cresol content 93 %) and an undetermined Cylindroiulus species (p-cresol content 51 %), in the brachyiulines Brachyiulus lusitanus (p-cresol content 21 %) and Megaphyllum fagorum (p-cresol content 92 %), as well as in an undescribed Typhloiulus species (p-cresol content 32 %, Leptoiulini). In all species, p-cresol was accompanied by small amounts of phenol. The secretion of M. fagorum was exclusively phenolic, whereas phenols were accompanied by benzoquinones in all other species. This is the first incidence of clearly phenol-dominated secretions in the Julidae. We hypothesize a shared biosynthetic route to phenols and benzoquinones, with benzoquinones being produced from phenolic precursors. The patchy taxonomic distribution of phenols documented herein supports multiple independent regression events in a common pathway of benzoquinone synthesis rather than multiple independent incidences of phenol biosynthesis. Electronic supplementary material The online version of this article (doi:10.1007/s10886-016-0680-4) contains supplementary material, which is available to authorized users.

Introduction
Millipedes are well protected against predators. Apart from hardened cuticles, disturbance-related coiling behaviors, or defensive bristles (Polyxenida), the majority of millipedes are known to release repellent and noxious fluids from serial exocrine glands, serving as an effective means of active defense. Depending on the taxonomic group, diplopod defensive secretions show considerable chemical diversity as comprehensively reviewed recently (Shear 2015). Briefly, Glomerida and Polyzoniida produce unique alkaloids (e.g., Meinwald et al. 1966Meinwald et al. , 1975Schildknecht et al. 1966;Shear et al. 2011;Wood et al. 2000), Polydesmida produce cyanogenic Electronic supplementary material The online version of this article (doi:10.1007/s10886-016-0680-4) contains supplementary material, which is available to authorized users. compounds Shear et al. 2007), whereas all groups of Juliformia mainly secrete quinones (e.g., Eisner et al. 1978;Vujisić et al. 2011). Indeed, the latter group -the Juliformia -have been known as Bquinone millipedes^ (Eisner et al. 1978), implying that this superorder almost exclusively produces quinone-based secretions. Interestingly, within the putative j uliformian sister gro up BPolydesmida (Chordeumatida (Stemmiulida + Callipodida))^several taxa rely on phenolic secretions (e.g., Blanke and Wesener 2014;Shear 2015). Callipodids, for instance, appear to exclusively produce phenols (e.g., Makarov et al. 2011), which give them a characteristic and obtrusive odor, easily noticeable by humans over distances of several meters. Additionally, stemmiulidans (Shear 2015) and several polydesmidans have been reported to discharge phenolics, and in both cases the most frequently occurring component was p-cresol Mori et al. 1994;Noguchi et al. 1997;Shear et al. 2007;Taira et al. 2003).
In many Arthropoda, the biosynthesis of phenols and benzoquinones is thought to be related. There are good examples of arthropods that utlize both phenolic and benzoquinonic compounds (e.g., Rocha et al. 2013). In laniatorean harvestmen, for instance, the secretions of representatives of basal grassatorean families rely on phenolics, whereas the secretions of derived grassatoreans may contain both phenols and benzoquinones or may even be purely benzoquinonic (Föttinger et al. 2010;Raspotnig et al. 2015). In laniatoreans, benzoquinones appear to present a derived character state, that can be produced from phenols by para-oxidation, and the production of benzoquinones may be considered an extension of the pathway to phenols (Raspotnig et al. 2015;Rocha et al. 2013).
In the scope of our studies on the evolutionary history of secretion chemistry in diplopods, it is essential to pinpoint basic correlations between the chemistry of different taxa. We here hypothesize that benzoquinones in juliformians evolved from the ancestral state of phenolic secretions, as still present in juliformian outgroups (Raspotnig and Bodner 2014). To test our idea, we conducted extensive chemical screening of julid secretions for their phenolic content. So far, phenolics in juliformians have been regarded to be an exception or even completely missing: only one representative of Julida, namely a member of the basal julidan family Parajulidae, Oriulus venustus (Wood 1864), was reported to discharge a phenol-rich secretion (Kluge and Eisner 1971). There are, however, an increasing number of reports on julid phenolics as minor, trace, or byproducts of the quinone-rich secretions of certain species (e.g., Sekulić et al. 2014).
We provide evidence that phenol-based secretions are more widespread in the Julidae, and that phenolics even prevail over quinones in some species of the tribes Cylindroiulini, Brachyiulini, and Leptoiulini.

Methods and Materials
Collection of Species Individuals, mostly adults, from 42 species belonging to 17 genera and 6 tribes of Julidae and 2 species of Blaniulidae (see supplemental Table S1) were collected by hand, either from the leaf litter layer or from deeper soil and breakstone beneath the leaf litter layer at various locations in Austria, Germany, Italy, France, Spain, Bulgaria, Serbia, and Azerbaijan. Vouchers were deposited at the Natural History Museum of Vienna (NHMW), Natural History Museum of Denmark (ZMUC), Hungarian Natural History Museum (HNHM), National Museum of Natural History Sofia (NMNHS), and at the Faculty of Biology, Institute of Zoology, University of Belgrade (FBIZO).
Extraction and Analysis of Defensive Secretions Secretions were obtained by whole body extraction of single individuals in hexane for 15 min. The defensive secretions were discharged directly into the solvent. Aliquots of diluted extracts (1.5 μl) were analyzed by gas chromatography-mass spectrometry (GC-MS), using a trace gas chromatograph coupled to a DSQ I mass spectrometer (MS), both from Thermo (Vienna, Austria). GC and MS conditions were the same as previously described (Bodner and Raspotnig 2012). Gas chromatographic retention indices (RI) of extract components were calculated using an alkane standard mixture (Van den Dool and Kratz 1963).
High-resolution mass spectrometry was carried out on a Q-exactive high-resolution Orbitrap MS from Thermo (Vienna, Austria). Samples containing secretion in hexane were gently reduced under nitrogen, then dissolved in methanol: water (1:1) with 1 % formic acid, and analyzed by direct infusion ESI-MS and HPLC-MS, respectively. Components were observed as [M + H] +. -ions as well as Na -and Kadducts.

Profile Evaluation and Statistics
Relative abundance of single components (in %) was calculated by integration of peak areas in the chromatograms, leading to individual secretion profiles. This semi-quantitative method to calculate secretion profiles is widely used in chemosystematic studies of different arthropod taxa (e.g., mites (Heethoff 2012;Sakata et al. 2003); opilionids (Hara et al. 2005); thrips (Suzuki et al. 1989); diplopods (Makarov et al. 2010)). Individual chromatographic profiles were compared eventually by non-metric multidimensional scaling (NMDS) using the Bray-Curtis coefficient of dissimilarity (Bray and Curtis 1957).

Compound Identification
The major phenolic compound in all 6 species appeared to be a methylated phenol isomer (= cresol: peak D; M + at m/z 108). The mass spectra of the three possible cresol isomers (p-, o-, m-cresol) are basically indistinguishable, at best showing slight differences in the intensity of M + (at m/z 108) and M-1 + -ions (at m/z 107), respectively. The retention index measured for compound D (RI = 1071) was clearly different from authentic o-cresol (RI = 1051), but corresponded to both the RI of authentic m-cresol (RI = 1072) as well p-cresol (RI = 1071). TMS-Derivatization of compound D, p-and m-cresol, respectively, led to cresol-TMS ethers, which again showed indistinguishable mass spectra: M + at m/z 180 (45), fragment ions at m/z 165 (100), 149 (5) From the secretions of B. lusitanus, Cylindroiulus sp., S. pelidnus, S. styricus, and Typhloiulus n. sp. additional 21 components, mainly benzoquinones, could be separated (Table 2, Fig. 1). Fourteen of the compounds were fully or at least partly identified, either by a comparison of GC-MS data to authentic standards, by a comparison of mass spectra and retention indices to data from literature, or by high resolution mass spectrometry, respectively (Table 2). These compounds comprised 1,4-benzoquinone and differentially substituted methyl-, hydroxy-, and methoxy-1,4-benzoquinones (peaks A, C, E, F, G, I, J, L, and M) as well as two hydroquinones (peaks H, M), all of which had been described previously from the secretions of various Juliformia (Shear 2015).
All other compounds (K, N, O, P, Q, R, S, T, U, V, and W) were, to our knowledge, new for millipede secretions. Only species in bol were investigated in this study. For species marked with * literature data are available (see Shear 2015;Vujisić et al. 2011Vujisić et al. , 2014. Species in bold and marked with * were reinvestigated   (21), 121 (7), 111 (19), 108 (7), 96 (7), 83 (24), 69 (13), 68 (17), 67 (7) 2,3-dimethoxy-5-methyl-1,4-benzoquinone   Radulović et al. (2010). b Isomers assigned according to Wu et al. (2007). c Tentatively identified on the basis of mass spectral fragmentation and high resolution mass spectrometry. d Peak M was specific for Brachyiulus lusitanus, containing 2 compounds, namely 2,3-dimethoxy-5-methylhydroquinone and methyl-paraben in a ratio of about 1:1. RIs measured for authentic 2,3-dimethoxy-5methylhydroquinone and methyl-paraben, respectively, proved to be indistinguishable (for both compounds RI 1455), and co-injection of both compounds (in 1:1 ratio) led to a single, sharp peak, showing a mass spectrum as observed for peak M. On the other hand, methyl-paraben (without 2,3-dimethoxy-5-methylhydroquinone) was found in the extracts of Typhloiulus n. sp. (peak N). e Molecular formula, based on high resolution mass measurement Compounds N and Q were identified as methyl-paraben and 2-phenylphenol, respectively. Compound W was partly identified: it exhibited a molecular ion at m/z 228 (base peak), together with an intense M + 2-ion, indicating the reduction of a quinone in the hot injector. The compound was first suspected to represent a 2,3,5,6-tetramethoxy- Compounds K, O, P, T, U, and V were not fully identified. These compounds shared the mass spectrometric characteristics of hydroxy-methoxy-1,4-benzoquinones (Budzikiewicz et al. 1967: p. 530). Possible structures, supported by high resolution mass spectrometry, are proposed in Table 2. The detailed chemical identification of these compounds will be presented in a separate paper. Compounds R and S remained unidentified.

Secretion Profiles
The 6 phenol-producing species exhibited highly consistent secretion profiles in terms of profile quality (= compound composition) as well as relative abundance of components. The chromatographic profiles are given in Table 3. Only the two species of Styrioiulus showed indistinguishable profiles, and a comparison of individual profiles based on non-metric multidimensional scaling (NMDS) Cylindroiulus sp.  Table 2. Note that the chromatographic response between 10.00 and 18.50 min retention time is amplified for a better demonstration of minor peaks resulted in a scatter plot, showing one single cluster (Fig. 2a). All other species were readily distinguishable by their characteristic secretion chemistry. For B. lusitanus, individuals from the same location exhibited slightly different but statistically distinguishable secretion patterns (Fig. 2b) in a repeated investigation after a time interval of one year. Statistically significant differences between female and male secretion pattern were not observed for any of the species.

Discussion
Phenols in Juliformian Millipedes? Although p-cresol and phenol have been reported sporadically as minor compounds in the quinone-rich secretions of julids, such as Unciger transsilvanicus (Uncigerini) , and are indicated for several species of Serboiulus (Leptoiulini), we here provide the first examples for clearly phenol-based chemical secretions (= phenolic content of secretion >20 %) in the family Julidae. In three species analyzed, phenolic content was higher than 90 %: in S. pelidnus and S. styricus about 95 %, and in M. fagorum the secretions were exclusively phenolic. Most interestingly, these phenol-producing species are not closely related, and the distribution of phenols does not follow an obvious taxonomic pattern. Species with phenolic secretions appear to be unexpectedly present in genera or tribes whose Bnormal^representatives rely on the common benzoquinonic chemistry. We found such Baberrant^, phenol-producing species in 5 genera, belonging to 3 different tribes of julids -Brachyiulini, Cylindroiulini, and Leptoiulini. So far, each of these tribes was known for uniform benzoquinonic chemistry. Taking the example of Cylindroiulini, hitherto analyzed species of Cylindroiulus (Huth 2000), Enantiulus (Huth 2000), and Allajulus (Bodner and Raspotnig 2012) showed non-phenolic, benzoquinonedominated secretions. Comparably, preliminary data indicate that the mono-specific cylindroiuline genus Kryphioiulus exclusively disharges benzoquinones as well. Thus, phenols appear to have arisen at least twice in cylindroiulines,  In this respect, it is important to recall the paper of Kluge and Eisner (1971), who reported on a phenol-rich secretion in the parajulid Oriulus venustus. Until now, this was the only report on a phenol-predominated secretion in the Juliformia. Assessing this report in light of new data, there is evidence that phenolic secretions are not exceptional in the Julida. Taking current data on julidan secretions as a basis (including literature data), we can currently list 7 species with phenol-dominated secretions out of 57 chemically investigated species. These belong to families Julidae, Blaniulidae, and Parajulidae (Table 1). If we include those species with phenols as minor compounds (3 additional species, Table 1), then phenol-producers comprise about 18 % of the Julida so far investigated. These data indicate that phenolic secretions among the Julida are no rarity and that they are to be expected in a number of additional taxa.

Phenol Biosynthesis and Evidence for a Shared Phenol
Origin Both benzoquinones and phenols are widespread compounds in the defensive secretions of arthropods. High selective pressure may have led to independent evolution of such compounds in groups such as Coleoptera, Blattaria, Dermaptera, Opiliones, and Diplopoda (Blum 1981(Blum , 1996. Additionally, within distinct taxa, it frequently is not clear whether phenolics and benzoquinones may have arisen independently in different sub-taxa, or whether they share a common ancestry (e.g., Caetano and Machado 2013; Raspotnig et al. 2015). In order to address such questions, information on the biosynthetic pathways leading to the compounds is important (Blum 1981). There are only a few studies dealing with the biosynthesis of phenols and benzoquinones in arthropods. In harvestmen, for instance, the biosynthesis of phenols and benzoquinones follows a common multi-step pathway, in the course of which the condensation of acetate and propionate units leads to phenols that subsequently give rise to benzoquinones via para-oxidation (Raspotnig et al. 2015;Rocha et al. 2013). Insects may produce benzoquinones differentially, but nevertheless retain the step of phenol oxidation: for example, the tenebrionid beetle Eleodes longicollis p r o d u c e s 1 , 4 -b e n z o q u i n o n e b y o x i d a t i o n o f dihydroxybenzene (1,4-hydroquinone), which in turn arises from arbutin, a hydroquinone-glucopyranosid (Happ 1968). Regarding millipedes, it has been assumed that benzoquinone synthesis relies on the availability of aromatic amino acids (Blum 1981). The polydesmidan Oxidus gracilis, for instance, produces HCN, benzaldehyde, but also phenol, guaiacol, and arbutin from tyrosine by tyrosine phenol lyase . Based on the occurrence of phenol tyrosine lyase in juliformian millipedes,  suggested a similar biosynthetic pathway to juliformian benzoquinones, basically leading to phenolics, then to hydroquinones via arbutin, then to benzoquinones via paraoxidation.
Evidence for Ancestral Chemical Equipment? Even though the putative sister group of the Juliformia is still in discussion (Enghoff 1984;Sierwald et al. 2003) there is evidence that close juliformian outgroups may be represented by Nematophora (comprising Callipodida, Stemmiulida, and Chordeumatida) and Polydesmida (Blanke and Wesener 2014;Miyazawa et al. 2014;Sierwald and Bond 2007). Interestingly, in these outgroups, the production of p-cresol is widespread or even characteristic (Shear 2015). Phenol biosynthesis requires a complex machinery of different enzymes, making the multiple independent development of the same compounds in closely related taxa less likely. Following this argument, phenolics may be considered the common, ancestral chemical components of juliformian, nematophoran, and polydesmidan defensive secretions. Particularly callipodidan secretions (generally phenol as minor, and p-cesol as major constituent) are reminiscent of findings for the Julidae (Ćurčić et al. 2009;Eisner et al. 1963;Makarov et al. 2011;Shear 2015;Shear et al. 2007Shear et al. , 2010. With respect to Juliformia and to Julida in particular, we thus hypothesize that benzoquinones arose from the ancestral state of phenolics, and that the oxidation-step to benzoquinones evolved later, possibly in early juliformians. This event led to the replacement of phenolics by quinones in most juliformian taxa. Benzoquinones thus may be younger than phenolics, and possibly arose in early juliformians before the split into orders Spirostreptida, Spirobolida, and Julida. This situation basically supports a scenario for diplopod chemosystematics as recently discussed by Shear (2015).
We thus consider the most likely explanation for the patchy, non-taxonomic distribution of phenol-based secretions across the Julida (and presumably in the remaining Juliformia) to be the result of the loss of the para-oxidation step from phenols to benzoquinones, i.e., the last step in the proposed common multi-step pathway to benzoquinone formation (Raspotnig et al. 2015). This loss may occur with the inactivation of a single enzyme, and is thus a parsimonious explanation compared to the possibility of multiple independent evolutions of multi-step pathways to phenolics in different juliformian taxa.


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Travelling between Two Worlds: Complement as a Gatekeeper for an Expanded Host Range of Lyme Disease Spirochetes

Evading innate immunity is a prerequisite for pathogenic microorganisms in order to survive in their respective hosts. Concerning Lyme disease spirochetes belonging to the Borrelia (B.) burgdorferi sensu lato group, a broad range of diverse vertebrates serve as reservoir or even as incidental hosts, including humans. The capability to infect multiple hosts implies that spirochetes have developed sophisticated means to counter the destructive effects of complement of humans and various animals. While the means by which spirochetes overcome the hosts immune defense are far from being completely understood, there is a growing body of evidence suggesting that binding of the key regulator of the alternative pathway, Factor H, plays a pivotal role for immune evasion and that Factor H is an important determinant of host specificity. This review covers (i) the contribution of complement in host-specificity and transmissibility of Lyme disease spirochetes; (ii) the involvement of borrelial-derived determinants to host specificity; (iii) the interplay of human and animal Factor H with complement-acquiring surface proteins of diverse borrelial species; and (iv) the potential role of additional animal complement proteins in the immune evasion of spirochetes.

Introduction
A plethora of human and animal pathogens including bacteria (e.g., Streptococcus pyogenes, S. pneumoniae, Staphylococcus aureus, S. suis, Neisseria meningitides, Yersinia enterocolitica, Leptospira interrogans, Treponema denticola, diverse Borrelia spp.), fungi (e.g., Candida albicans), and parasites (e.g., Plasmodium falciparum) have developed sophisticated strategies to counteract complement as a means of evading a host´s innate immunity [1][2][3]. A central immune evasion strategy utilized by many pathogenic microorganisms involves the recruitment of the fluid phase complement regulator Factor H to the microbial surface to deregulate or inhibit the activation of the alternative complement pathway (see below). Many Factor H-binding proteins have been identified and characterized (e.g., the M protein of group A streptococci [4], PspC of pneumococci [5], PorB of N. meningitides [6], PorA1 of N. gonorrhoeae [7], YadA of Y. enterocolitica [8], LfHA of L. interrogans [9], FhbB of T. denticola [10], Complement regulator-acquiring surface proteins (CRASP) of Borrelia [11], and Pra1 of C. albicans [12]). Factor H consists of 20 so-called complement control protein (CCP) domains. Domains CCP6-8 at the N-terminus and CCP19-20 at the C-terminus are used for host cell recognition, whereas domains CCP1-4 are responsible for cofactor and decay accelerating activity. Microbial Factor H-binding proteins preferentially bind to CCP6-8 and CCP19-20 domains, thus, highlighting the role of these structures as a "hot spot of interaction" between human pathogens and Factor H [13]. Activation of the complement system. Complement is activated in a sequential manner by three pathways: the classical, lectin, and alternative pathway. The classical pathway is initiated by binding of the C1 complex consisting of one molecule of C1q, two molecules of C1r, and two molecules of C1s to immunoglobulins (IgM, IgG) bound to their corresponding antigens. Activated C1s cleaves C4 which, upon covalent binding to the target surface, cleaves C2 leading to the formation of the C3 convertase C4b2b of the classical pathway. Activation of the lectin pathway is triggered by binding of mannan-binding lectin (MBL), ficolins (H-ficolin, L-ficolin, M-ficolin) or collectin K-1 associated with MBL-associated serine proteases MASPs to a variety of carbohydrates of microbial origin. MASP-1 and MASP-2 (MASP) are able to cleave C4 and then C2 to form the same C3 convertase. The alternative pathway is initiated by covalent binding of C3b molecules to foreign particles (opsonization). Surface-bound C3b molecules recruit Factor B (FB) leading to the formation of a C3bB complex. Following cleavage of FB by Factor D (FD), the C3 convertase (C3bBb) of the alternative pathway is generated. This enzyme cleaves C3 molecules into the small C3a fragment (anaphylatoxin) and C3b which covalently binds in close vicinity of the newly formed C3 convertases, thereby resulting in a strong amplification loop that generates an increasing number of highly reactive C3b molecules. Binding of C3b to C4b and C3b within the C3 convertase of the classical and alternative pathway leads to the formation of the C5 convertase (C4b2b3b and C3bBb3b). Binding of the additional C3b molecule changes the substrate specificity of these enzymes towards C5 which subsequently is cleaved into C5b and the most potent anaphylatoxin, C5a. Generation of C5b initiates the activation of the terminal pathway by sequential binding of C6, C7, C8, and C9 to C5b. Upon binding of multiple C9 molecules (C9 polymerization) the pore-forming terminal complement complex (TCC) integrates into the membrane and leads to lysis of susceptible cells. The soluble regulators that control activation at the level of complement initiation (C1-INH) act Figure 1. Activation of the complement system. Complement is activated in a sequential manner by three pathways: the classical, lectin, and alternative pathway. The classical pathway is initiated by binding of the C1 complex consisting of one molecule of C1q, two molecules of C1r, and two molecules of C1s to immunoglobulins (IgM, IgG) bound to their corresponding antigens. Activated C1s cleaves C4 which, upon covalent binding to the target surface, cleaves C2 leading to the formation of the C3 convertase C4b2b of the classical pathway. Activation of the lectin pathway is triggered by binding of mannan-binding lectin (MBL), ficolins (H-ficolin, L-ficolin, M-ficolin) or collectin K-1 associated with MBL-associated serine proteases MASPs to a variety of carbohydrates of microbial origin. MASP-1 and MASP-2 (MASP) are able to cleave C4 and then C2 to form the same C3 convertase. The alternative pathway is initiated by covalent binding of C3b molecules to foreign particles (opsonization). Surface-bound C3b molecules recruit Factor B (FB) leading to the formation of a C3bB complex. Following cleavage of FB by Factor D (FD), the C3 convertase (C3bBb) of the alternative pathway is generated. This enzyme cleaves C3 molecules into the small C3a fragment (anaphylatoxin) and C3b which covalently binds in close vicinity of the newly formed C3 convertases, thereby resulting in a strong amplification loop that generates an increasing number of highly reactive C3b molecules. Binding of C3b to C4b and C3b within the C3 convertase of the classical and alternative pathway leads to the formation of the C5 convertase (C4b2b3b and C3bBb3b). Binding of the additional C3b molecule changes the substrate specificity of these enzymes towards C5 which subsequently is cleaved into C5b and the most potent anaphylatoxin, C5a. Generation of C5b initiates the activation of the terminal pathway by sequential binding of C6, C7, C8, and C9 to C5b. Upon binding of multiple C9 molecules (C9 polymerization) the pore-forming terminal complement complex (TCC) integrates into the membrane and leads to lysis of susceptible cells. The soluble regulators that control activation at the level of complement initiation (C1-INH) act as cofactors for FI-mediated inactivation of C3b (Factor H) or C4b (C4BP), and prevent formation of the TCC and integration of the complex into the membrane (vitronectin). In nature, the enzootic vertebrate-host transmission cycle of LD Borrelia involves ticks as the primary vectors, infecting a diverse group of both wild and domestic vertebrate hosts, including rodents, small mammals, dogs, goats, cattle, sheep, horses, deer, reptiles, and avian hosts [27][28][29][30][31][32][33][34][35][36][37][38][39][40]. While competent reservoir hosts are often persistently infected by spirochetes, incompetent hosts, including humans, are only susceptible to incidental borrelial infection. Notably, a reservoir host may be competent for a specific genospecies but incompetent for another, indicating that the classification of a particular vertebrate host as a "competent reservoir" should be used with caution (Table 1). It is also well-known that distinct hosts differ in their attractiveness to host-seeking ticks and in their susceptibility to different borrelial species (e.g., B. garinii preferentially parasitizes birds but does not infect rodents, while B. lusitaniae has been predominately isolated from lizards) [41][42][43][44][45]. Concerning differences in reservoir competence, there is an obvious correlation between the adaptation of spirochetes to perpetuate in distinct vertebrate hosts and their ability to counter the innate immune system, in particular, the complement of the infected hosts [31,[46][47][48][49][50][51] (Table 1). Hence, the serum resistance/sensitivity pattern of a particular genospecies plays a significant role for host-specificity. It also underpins the concept of a selective transmission driven by certain factors, most likely host complement, and thereby has a strong impact both on the dispersal and the global ecology of spirochetes. In addition, it has also been shown that the borreliacidal activity of the complement of a particular host appears to have a prophylactic effect by selectively eliminating spirochetes in the midgut of feeding ticks prior to transmission to the vertebrate host [52,53]. The destruction of susceptible spirochetes in the midgut of infected ticks may have a strong implication on the transmission dynamics as complement would prevent transstadial transmission of spirochetes to the next developmental stage of the tick, resulting in a pathogen-free vector.
Consistent with the current data available from in vitro studies with various animal sera, as well as borrelial isolates belonging to the B. burgdorferi sensu lato group, an obvious systematism has emerged, supporting the notion of a direct association between spirochete transmissibility and complement susceptibility. For example, B. garinii and B. valaisiana, both of which are known to be adapted to avian hosts, are highly susceptible to rodent sera; conversely, B. afzelii, B. spielmanii, B. japonica, B. bissettii, and B. bavariensis, all of which are adapted to rodents, are highly susceptible to avian complement but resist complement-mediated killing by rodent and human serum (Table 1) [31,[54][55][56][57]. By contrast, B. burgdorferi, a less specialized genospecies with an expanded host range, does not display a clear species-specific transmission pattern, instead pursuing the strategy of a "generalist", infecting a variety of vertebrate hosts. The broader spectrum of transmissibility may also explain the pattern of an intermediate serum-resistant phenotype displayed by B. burgdorferi when cells were challenged with different animal sera collected from avian, rodent, and ruminant hosts, respectively [31,46,48,49]. Of note, the phenotypic categorization of a borrelial strain or isolate to be serum-sensitive, intermediate serum sensitive/resistant, as well as serum-resistant is largely influenced by at least five important, mainly technical parameters (e.g., method of choice, origin of serum, sampling and storage of serum, serum concentration, and the specific borrelial strain investigated), making it somewhat difficult to compare the data published in different studies. For instance, B. garinii isolates belonging to different OspA serotypes were either highly sensitive or showed an intermediate serum-resistant phenotype upon incubation with the serum from the same animal host or with human serum [46]. In terms of human serum, concentrations below 20% lack any bactericidal activity against borrelial cells, which are not killed efficiently until concentrations higher than 40% are reached; thus, serum applied in lower amounts has obviously no discriminating power for the classification of borrelial genospecies [54,57]. Also, the complement activity of distinct animal sera is strongly dependent on the sampling and storage conditions, as it is well-known that, for example, mouse complement is extremely unstable, in particular the classical pathway [58]. For most animal sera studied, the complement activity has not been analyzed prior to using the sera in functional assays, probably due to the lack of validated test systems.

Species-Specific Factors Contributing to Host Specificity of Lyme Disease Spirochetes
As innate immunity, namely complement, is a prominent determinant of host specificity of Borreliae, various attempts have been undertaken to investigate the underlying molecular mechanisms and the critical factors involved in conferring complement resistance [59][60][61][62][63]. First and foremost, pioneering studies on complement resistance to human serum disclosed that the acquisition of complement regulators of the alternative pathway perfectly matched the serum resistance patterns of B. burgdorferi, B. afzelii, and B. spielmanii [59,62,64,65]. Recruitment of the key regulators of the alternative pathway, Factor H and Factor H-like protein 1 (FHL-1), by resistant spirochetes is of physiological relevance, as the Borrelia-bound proteins maintain their complement regulatory activity, thereby promoting the inactivation of the central complement component C3 and the termination of all downstream processes. Inhibition of the formation of the bacteriolytic TCC and its integration into the bacterial membrane efficiently protects borrelial cells from complement-mediated killing and, finally, clearance by the host's immune system [59,62]. Conversely, serum-sensitive B. garinii, B. valaisiana, B. andersonii, as well as B. lusitaniae lack the capability to bind human Factor H and FHL-1, underpinning the pivotal role of these complement inhibitory proteins in determining serum resistance of Lyme disease Borrelia, with the exception of B. bavariensis, which employs an independent strategy to overcome complement [59,62,64,[66][67][68]. Circumventing the host's self-defense mechanisms by acquiring Factor H appears to be a general strategy used by Borreliae, as comparative analysis revealed that diverse borrelial species were capable of binding to Factor H from different animals, including mouse, rat, cat, dog, and sheep. Interestingly, the binding of Factor H from horse, guinea pig, and cattle have not been observed [56,[69][70][71][72][73][74][75] (Table 2). Further studies have shown that B. burgdorferi is able to bind to Factor H from dog, goat, and cattle [74], as well as from monkey, mini pig, guinea pig, and pig, but not from duck and chicken [72]. When evaluating the published data, it has to be mentioned that in all of the performed studies, Far-Western blot analyses were performed using either denatured proteins (cell lysates or purified proteins) for capturing Factor H from different animal sera, or denatured serum proteins were immunoblotted and probed with Factor H-binding proteins (see paragraph below) as "prey" molecules [56,70,72,74,75]. While Far-Western blot analysis has been proven to be an elegant approach for detecting protein-protein interactions [76], in particular for the screening of potential, yet unknown ligands, the utilization of partially misfolded proteins as "bait" molecules might lead to false-positive results, as recently demonstrated for the interaction of human Factor H with OspE proteins [77,78]. Thus, it is prudent to confirm the data generated by this particular methodology by an additional approach using non-denatured proteins or, if possible, genetically modified cells producing the native protein on the bacterial surface. In closing, the overall Factor H binding pattern mainly resembles the pattern of serum resistance/susceptibility observed among Lyme disease spirochetes corroborating the hypothesis of a species-specific, complement-associated host selectivity.
A series of studies clearly demonstrated that purified, as well as surface-exposed, CspA of B. burgdorferi s.s. and B. afzelii bind to human Factor H [75,82,[87][88][89] while contradictory data have been reported for the binding of mouse Factor H to CspA, perhaps owing to the different approaches used to assess the protein-protein interactions [75,89]. Furthermore, binding of Factor H from other competent hosts (dog, rat, rabbit, cat, sheep, horse, cow) has not been observed, leading to the conclusion that CspA might not play a prominent role in immune evasion in these potential reservoirs [75]. Considering that humans are accidental hosts for spirochetes, the specific role of CspA and its strong potential to inactivate human complement [62,88,90] remains to be elucidated, in particular as CspA is required for the colonization of spirochetes at early stages of infection (tick-to-mammal transmission) and is produced during mammal-to-tick transmission stages, but is not synthesized during established infection [91,92]. In vitro studies also revealed that CspA encoding genes of B. burgdorferi and B. afzelii are upregulated after 48 h following a challenge with human, mouse, and dog serum [93].
Concerning CspA orthologs belonging to the Pfam54 protein family, binding of human Factor H and FHL-1 has only been observed for CspA of B. afzelii and B. spielmanii, but not for their paralogs, as well as for the orthologs of B. garinii, B. valaisiana, B. andersonii, and B. lusitaniae [66,67,70,84]. A putative CspA ortholog of B. bavariensis interacting with murine Factor H has been identified by Far-Western blotting following mass spectrometry and de novo sequencing [70]. Furthermore, B. bissettii and B. japonica produce proteins with molecular weights (26-28 kDa) comparable to the CspA proteins of B. burgdorferi (25.9 kDa) and B. afzelii (27.5 kDa), both of which display binding capabilities for murine Factor H [70] supporting the notion of a species-specific Factor H binding pattern for CspA. Sequence polymorphisms within the interacting binding site of the different Factor H proteins or CspA orthologs are most likely responsible for the binding specificities.
Like CspA of B. burgdorferi, CspZ strongly binds functionally active Factor H and FHL-1 from human serum and is able to protect borrelial cells from complement-mediated killing [86,94]. This particular molecule is highly conserved among B. burgdorferi isolates and is also capable of binding Factor H derived from mouse, rabbit, sheep, pig, and cow but exhibits considerably different binding properties [95] (Table 3). In contrast, CspZ orthologs identified in B. garinii and B. afzelii bound neither Factor H from these animals nor Factor H of human origin, and thus it appears highly unlikely that these molecules contribute to immune evasion through interaction with this specific complement regulator. However, CspZ orthologs may still have an impact on species-specific host-pathogen interactions by binding as yet unknown serum proteins [95]. Further studies are required to unambiguously determine whether the respective proteins interact with factor H; a binding of human and animal factor H to purified proteins was assessed by different Western blotting approaches [70,72,75,77,78,88,89,95]; ND, no data available; Bb, B. burgdorferi s.s.; Ba, B. afzelii; Csp, complement regulator-acquiring surface protein; Erp, OspE/F-related protein; synonyms of protein names are indicated in brackets.
Binding of murine Factor H to Erp proteins has been reported by different investigators employing various approaches for detecting protein-protein interactions [69][70][71]100], while others were unable to confirm binding of murine Factor H to Erp orthologs, thereby leading to the assumption that mice per se are probably not an appropriate model to study Factor H-mediated immune evasion [72]. Furthermore, these authors showed that ErpA and ErpP differ in their ability to bind Factor H from different animals (Table 3), thus suggesting that sequence variations among Erp proteins are responsible for the species-specific Factor H binding pattern [72]. Additional Factor H-binding proteins, potentially belonging to the Erp protein family, due to the similar molecular weights, have been identified among B. afzelii, B. garinii, B. bavariensis, B. valaisiana, and B. andersonii. These were shown to bind to Factor H derived from mice, rats, dogs, or cats [70]. Comparative sequence analysis of a range of B. burgdorferi strains revealed multiple Erp proteins exhibiting a larger or smaller degree of amino acid sequence identity, which can be simultaneously produced by individual bacteria. These proteins are believed to possess different functions and could in theory contribute to the pathogenesis of Lyme disease spirochetes (e.g., by binding to Factor H of distinct animal species), as has been shown for ErpG, ErpX, and ErpY [74]. The considerable sequence variation and the restricted species-specific binding pattern of Factor H may constitute further evidence for a role of this complement regulator in immune evasion of spirochetes in different reservoir hosts. Pursuing the concept of Factor H-mediated immune evasion as an important factor in spirochete ecology, it should follow that the Factor H binding pattern should match the serum resistance phenotype of the respective genospecies. As depicted in Table 4, there is indeed a striking correlation between Factor H-binding and serum resistance for most borrelial species and sera analyzed, except for B. bavariensis in human, rat, cat, and dog serum, B. afzelii in rat serum, B. valaisiana and B. japonica in cat serum, as well as B. bissettii in dog serum. Concerning B. bavariensis, it has recently been shown that two CspA orthologs, BGA66 and BGA71, inhibit complement activation of human serum independently of binding of Factor H by direct interaction with the terminal pathway, resulting in inhibition of TCC assembly [68]. As the inhibitory capacity of BGA66 and BGA71 on animal sera has not been investigated yet, it is impossible to make a final conclusion concerning host specificity drawn from the data available. Of note, it is well-known that spirochetes tend to lose plasmids during continuous cultivation, thus depending on the genetic composition, the borrelial strains used in the different studies may or may not produce various Factor H-binding proteins. This might also be an explanation for the discrepancies observed between different studies. As expected, a strict correlation could not be found for borrelial strains displaying an intermediate serum-resistant phenotype in the corresponding sera. More importantly, the inability to bind to Factor H correlated well with a serum susceptible phenotype (Table 4), underlining the importance of Factor H-dependent complement evasion by Borreliae in their diverse hosts. human complement by binding to Erp proteins during certain stages of infection remains to be determined.
Binding of murine Factor H to Erp proteins has been reported by different investigators employing various approaches for detecting protein-protein interactions [69][70][71]100], while others were unable to confirm binding of murine Factor H to Erp orthologs, thereby leading to the assumption that mice per se are probably not an appropriate model to study Factor H-mediated immune evasion [72]. Furthermore, these authors showed that ErpA and ErpP differ in their ability to bind Factor H from different animals (Table 3), thus suggesting that sequence variations among Erp proteins are responsible for the species-specific Factor H binding pattern [72]. Additional Factor H-binding proteins, potentially belonging to the Erp protein family, due to the similar molecular weights, have been identified among B. afzelii, B. garinii, B. bavariensis, B. valaisiana, and B. andersonii. These were shown to bind to Factor H derived from mice, rats, dogs, or cats [70]. Comparative sequence analysis of a range of B. burgdorferi strains revealed multiple Erp proteins exhibiting a larger or smaller degree of amino acid sequence identity, which can be simultaneously produced by individual bacteria. These proteins are believed to possess different functions and could in theory contribute to the pathogenesis of Lyme disease spirochetes (e.g., by binding to Factor H of distinct animal species), as has been shown for ErpG, ErpX, and ErpY [74]. The considerable sequence variation and the restricted species-specific binding pattern of Factor H may constitute further evidence for a role of this complement regulator in immune evasion of spirochetes in different reservoir hosts. Pursuing the concept of Factor H-mediated immune evasion as an important factor in spirochete ecology, it should follow that the Factor H binding pattern should match the serum resistance phenotype of the respective genospecies. As depicted in Table 4, there is indeed a striking correlation between Factor H-binding and serum resistance for most borrelial species and sera analyzed, except for B. bavariensis in human, rat, cat, and dog serum, B. afzelii in rat serum, B. valaisiana and B. japonica in cat serum, as well as B. bissettii in dog serum. Concerning B. bavariensis, it has recently been shown that two CspA orthologs, BGA66 and BGA71, inhibit complement activation of human serum independently of binding of Factor H by direct interaction with the terminal pathway, resulting in inhibition of TCC assembly [68]. As the inhibitory capacity of BGA66 and BGA71 on animal sera has not been investigated yet, it is impossible to make a final conclusion concerning host specificity drawn from the data available. Of note, it is well-known that spirochetes tend to lose plasmids during continuous cultivation, thus depending on the genetic composition, the borrelial strains used in the different studies may or may not produce various Factor H-binding proteins. This might also be an explanation for the discrepancies observed between different studies. As expected, a strict correlation could not be found for borrelial strains displaying an intermediate serum-resistant phenotype in the corresponding sera. More importantly, the inability to bind to Factor H correlated well with a serum susceptible phenotype (Table 4), underlining the importance of Factor H-dependent complement evasion by Borreliae in their diverse hosts.

Interaction of Borreliae with Additional Complement Proteins
Binding of additional serum factors, in particular complement regulatory proteins, may also have an impact in facilitating serum resistance of Lyme disease spirochetes. It has recently been shown that B. burgdorferi is able to directly interact with the C1 complex through the outer surface protein BBK32. Additionally, Borreliae can interact with components of the TCC through CspA, resulting in an efficient termination of the classical and terminal pathway, thus protecting spirochetes from being killed by human complement [90,101]. Concerning C1-INH, which is known to bind to relapsing fever spirochetes [102], there is no evidence of an interaction of Lyme disease spirochetes with this particular regulator of the classical and lectin pathway [67,68,103]. Binding of native C4BP, the key complement regulator of the classical pathway, has been reported for B. burgdorferi and B. garinii [104]. Furthermore, recombinant human C4BP has been shown to bind to B. burgdorferi, B. afzelii, B. garinii, B. bavariensis, and, to a somewhat weaker extent, to B. valaisiana, B. lusitaniae, B. bissettii, and B. japonica using a Far-Western blot approach [103]. The same authors also observed binding of recombinantly produced ovine C4BP to B. burgdorferi, while none of the tested borrelial strains bound to recombinantly produced bovine C4BP. Further analyses revealed that several borrelial species, including B. afzelii, B. garinii, B. bavariensis, and B. andersonii, appear to interact with recombinantly produced human vitronectin, a specific inhibitor of the terminal pathway, but not with vitronectin of ovine or bovine origin [103]. Pull down assays using recombinant complement regulators following mass spectrometry led to the identification of several proteins interacting with human Factor H (CspA orthologs of B. burgdorferi and B. afzelii, BG0407 of B. bavariensis), C4BP (hypothetical outer surface proteins of B. afzelii, B. burgdorferi and B. garinii, OspA of B. burgdorferi), and vitronectin (variable large protein of B. garinii) [103]. Future studies are necessary to confirm binding of these complement regulators to the respective borrelial proteins, using native complement proteins in order to determine the biological relevance of the observed protein-protein interaction in the context of the well-known resistance patterns of the respective borrelial species.

Future Perspectives
Over the past 15 years, numerous proteins of Lyme disease spirochetes have been described that interact specifically with human complement whereby a few studies also focused on the identification of proteins interacting with serum components of various animals [11,47,70,83,101]. There is a growing body of evidence suggesting an important role for the innate immune system of a particular host in determining the transmissibility and the overall dispersal of spirochetes. However, only fragmentary information is available on specific borrelial-derived determinants that are crucial for evading complement as the first line of host defense.
Comprehensive proteomics analyses, including expression and interaction proteomics, may foster the identification of potential complement-interacting proteins of spirochetes as well as other important veterinary pathogens (Babesia spp., Streptococcus equi, Mycobacterium spp., Rickettsia spp.). Of note, whenever practical, a thorough biochemical analysis should be conducted to further characterize and quantify protein-protein interactions by different approaches (e.g., ELISA, isothermal calorimetry, surface-plasmon resonance, or microscale thermophoresis, whereby the latter grants measurement of biomolecular interaction under immobilization-free, close-to-native conditions) [105]. Furthermore, one should always bear in mind that the collected data have to be carefully interpreted in the light of a rational syllogism.

Conclusions
Lyme disease spirochetes have developed an array of sophisticated strategies to establish infection and to circumvent host innate immunity by fending off host complement attack through acquisition of soluble complement regulators of different vertebrate hosts. In particular, the species-specific binding patterns of Factor H, in the majority of cases, matches the serum resistance phenotype of the respective borrelial genospecies, thereby suggesting that this molecular interaction plays an important role in immune evasion of Lyme disease spirochetes during the transmission cycles of various vertebrate hosts. Moreover, Borreliae exploit further strategies, namely the direct interaction with complement components to manipulate, influence, and terminate complement activation. As this scenario has only been described for human complement, similar interaction profiles can be expected for animal-derived components. Clearly, animal complement regulators are able to bind to different borrelial proteins, and further studies are required to validate the biological relevance of the interactions in vitro as well as in vivo. However, the hypothesis of a complement-mediated selection determining the host range of a particular borrelial species presented here requires reconciliation with the conflicting observations described. In closing, further investigations will undoubtedly contribute to an increased understanding of how Borreliae persistently infect their hosts and which specific determinants are involved and responsible for survival and persistence.