text:
Proteomic Analysis of Solid Pseudopapillary Tumor of the Pancreas Reveals Dysfunction of the Endoplasmic Reticulum Protein Processing Pathway*

Solid pseudopapillary tumor of the pancreas (SPTP) is a low-grade malignant tumor with a favorable prognosis after surgery. Many previous studies have focused on clinical features or pathological biomarkers of the disease, but a better understanding of the molecular mechanisms underlying SPTP may help guide future therapeutic strategies. Here, we used isobaric tags for relative and absolute quantitation (iTRAQ) technology integrated with liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis to identify differentially expressed proteins in SPTP specimens. A total of 1171 proteins with a threshold of a 1.5-fold change and a p value ≤ 0.05 between SPTP tissue and matched normal pancreas tissue were identified for bioinformatics analysis. Mass spectrometry results were then further confirmed by assessing six representative proteins (ACADL, EPHX2, MSI2, DKK4, JUP, and DAD1) in individual specimens with immunohistochemistry. Upon mapping of the differentially expressed proteins to the Kyoto Encyclopedia of Genes and Genomes pathways database, we found several new cell-adhesion molecules that could be used as pathologic biomarkers. Furthermore, we observed that many endoplasmic reticulum-associated proteins were altered, suggesting that endoplasmic reticulum stress may play an important role in SPTP tumorigenesis. Seven proteins (ERO1LB, TRIM1, GRP94, BIP, SEC61B, P4HB, and PDIA4) in this pathway were further validated by immunohistochemistry, and six of them (except SEC61B) coincided to the LC-MS/MS results. This first comprehensive analysis of the SPTP proteome confirms proteins that have been implicated in earlier reports and reveals novel candidates and pathways that could be investigated further for clinical applications.

Solid pseudopapillary tumor of the pancreas (SPTP) 1 is an uncommon epithelial neoplasm of low malignant potential that occurs predominantly in young women. It was first described by Frantz in 1959 as a solid and cystic lesion that was previously misdiagnosed as a rare islet tumor or as an acinar cell carcinoma (1). The incidence of SPTP is relatively low and accounts for ϳ1-2% of all pancreatic tumors. Most patients with the disease do not have significant symptoms until the volume of the tumor is very large or present with other complications. In 1996, the World Health Organization (WHO) reclassified SPTP as a low-grade malignant tumor because of its biological behavior (2). Fortunately, the tumor is confined to the pancreas in 85% of patients. Patients with SPTP have a favorable prognosis after complete excision, with a 5-year survival rate of 85%. Even the 15% of patients with recurrent SPTP or with liver or peritoneal metastasis or invasion generally have good long-term survival (3)(4)(5).
The reported incidence of SPTP has increased with improved detection methods in the last decade, and much pathologic and clinical effort has been aimed at understanding the origin and development of SPTP. In a large-scale study at Ruijin Hospital, a total of 82 cases of SPTP were studied retrospectively. The authors concluded that SPTP with incomplete capsules often presented with malignant behavior and hypothesized that SPTP was probably caused by disordered pancreatic stem cell development (6). Another group at the University of Kiel analyzed 59 patients and postulated that SPTP might be derived from genital ridge/ovarian anlage-related cells (7). Moreover, sex hormone receptors, such as progesterone receptor (PR), have been evaluated by IHC. Nearly 80% of the SPTP specimens (22/28) have high positive staining for PR (8), indicating that abnormal activation of the progesterone pathway may contribute to the disease. At the molecular level, most findings have centered on aberrant WNT pathway activity. For example, mutations of CTNNB1 were the only apparent mutations identified by wholeexome sequencing of tumors from eight patients with SPTP (9). Muller-Hocker et al. have also shown via IHC that some cell-cycle associated proteins are down-regulated in SPTP tissue (10). However, the SPTP proteome has not yet been systemically analyzed.
Current SPTP diagnosis and treatment methods are based on traditional histopathologic examination and clinical features. Although some useful SPTP biomarkers such as CD99, CD10, and E-cadherin have been identified in previous studies (11)(12)(13)(14), there are still many problematic cases in which a panel of these pathologic markers is insufficient to distinguish SPTP. Furthermore, proteomic characterization of SPTP will allow both researchers and clinicians to understand the disease much better, which may be useful to develop nonsurgical treatments in the future. Gel-Free approaches (e.g. LC-MS/MS) integrated with iTRAQ represent a new technology for measuring expression levels of different proteins that has been widely used in the analysis of clinical tissues. Numerous studies have used this technology to identify new biomarkers and pathways for many diseases. The aim of this study was to build a high-confidence, novel protein biomarker panel from our large set of clinical SPTP specimens. We analyzed differentially expressed proteins in SPTP specimens by using LC-MS/MS mass spectrometry and iTRAQ labeling and identified 1171 proteins whose expression significantly differed (Ͼ1.5fold change and p value Ͻ0.05) between normal pancreas tissue and SPTP samples. Our findings that the endoplasmic reticulum protein processing pathway is potentially associated with SPTP pathogenesis can be further investigated by researchers and clinicians.

EXPERIMENTAL PROCEDURES
Sample Collection-All specimens were collected at the time of surgery at the Department of General Surgery, Institute of Digestive Surgery, Ruijin Hospital, Shanghai JiaoTong University Medical School and deposited in liquid nitrogen. All samples were obtained from the patients with informed consent and with approval of the institutional ethics committee. Of specimens with a pathologic diagnosis of SPTP, we chose five normal-tumor tissue pairs from five different individuals (supplemental Table S1) for proteomic analysis.
Protein Preparation-All samples were homogenized in lysis buffer (4% SDS, 1 mM DTT, 150 mM Tris-HCl pH 8.0, and protease inhibitor). After 3 min incubation in boiling water, the homogenate was sonicated on ice. The crude extract was then incubated in boiling water again and clarified by centrifugation at 16,000 ϫ g at 25°C for 10 min. Protein content was determined with the BCA protein assay reagent (Beyotime, Shanghai, China).
Protein Digestion and iTRAQ Labeling-Protein digestion was performed according to the filter-aided sample preparation procedure described by Wisniewski et al. (15) and the resulting peptide mixture was labeled using the 8-plex iTRAQ reagent according to the manufacturer's instructions (Applied Biosystems, Foster City, CA). Briefly, 200 g of proteins for each sample were incorporated into 30 l Buffer X (4% SDS, 100 mM DTT, and 150 mM Tris-HCl pH 8.0). The detergent, DTT, and other low-molecular-weight components were removed using Buffer Y (8 M Urea and 150 mM Tris-HCl pH 8.0) by repeated ultrafiltration (Microcon units, 30 kDa). Next, 100 l 0.05 M iodoacetamide in Buffer Y was added to block reduced cysteine residues and the samples were incubated for 20 min in darkness. The filters were washed with 100 l buffer Y three times and then washed twice with 100 l Buffer Z (50 mM triethylammonium bicarbonate at pH 8.5). Finally, the protein suspensions were digested with 2 g trypsin (Promega, Madison, WI) in 40 l Buffer Z overnight at 37°C and the resulting peptides were collected as a filtrate. The peptide content was estimated by UV light spectral density at 280 nm. The peptides from normal pancreas and matched SPTP were respectively mixed as a pool and then equally divided into three fractions (normal pancreas: N1, N2,and N3; SPTP: T1, T2, and T3). A standard pool comprising a mixture of equal amounts of protein derived from all samples served as an internal control (IS). The samples were labeled as IS-113, N1-114, N2-115, N3-116, T1-117, T2-118, and T3-119, and were multiplexed and vacuum dried. For labeling, each iTRAQ reagent was dissolved in 70 l of ethanol and added to the respective peptide mixture.
Peptide Fractionation with Strong Cation Exchange (SCX) Chromatography-iTRAQ-labeled peptides were fractionated by SCX chromatography using the AKTA Purifier system (GE Healthcare). The dried peptide mixture was reconstituted and acidified with 2 ml Buffer A (10 mM KH 2 PO 4 in 25% of ACN, pH 2.7) and loaded onto a PolySULFOETHYL 4.6 ϫ 100 mm column (5 m, 200 Å, PolyLC Inc, Columbia, MD). The peptides were eluted at a flow rate of 1 ml/min with a gradient of 0 -10% Buffer B (500 mM KCl and 10 mM KH 2 PO 4 in 25% of ACN, pH 2.7) for 7 min, 10 -20% Buffer B for 10 min, 20 -45% Buffer B for 5 min, and 45-100% Buffer B for 5 min. The elution was monitored by absorbance at 214 nm, and fractions were collected every 1 min. The collected fractions (about 30 fractions) were finally combined into 10 pools and desalted on C18 Cartridges (Empore™ SPE Cartridges C18 (standard density), bed I.D. 7 mm, volume 3 ml, Sigma). Each fraction was concentrated by vacuum centrifugation and reconstituted in 40 l of 0.1% (v/v) trifluoroacetic acid. All samples were stored at Ϫ80°C until LC-MS/MS analysis.
Liquid Chromatography (LC) -Electrospray Ionization (ESI) Tandem MS (MS/MS) Analysis by Q Exactive-Experiments were performed on a Q Exactive mass spectrometer that was coupled to Easy nLC (Proxeon Biosystems, now Thermo Fisher Scientific). 10 l of each fraction was injected for nanoLC-MS/MS analysis. The peptide mixture (5 g) was loaded onto the C18-reversed phase column (Thermo Scientific Easy Column, 10-cm long, 75-m inner diameter, 3-m resin) in Buffer A (0.1% formic acid) and separated with a linear gradient of Buffer B (80% acetonitrile and 0.1% formic acid) at a flow rate of 250 nL/min controlled by IntelliFlow technology over 140 min. MS data was acquired using a data-dependent top10 method dynamically choosing the most abundant precursor ions from the survey scan (300 -1800 m/z) for higher energy collisional dissociation (HCD) fragmentation. Determination of the target value is based on predictive Automatic Gain Control (pAGC). Dynamic exclusion duration was 60 s. Survey scans were acquired at a resolution of 70,000 at m/z 200 and resolution for HCD spectra was set to 17,500 at m/z 200. Normalized collision energy was 30 eV and the underfill ratio, which specifies the minimum percentage of the target value likely to be reached at maximum fill time, was defined as 0.1%. The instrument was run with peptide recognition mode enabled.
Sequence Bioinformatic Analysis-The sequence data of the selected differentially expressed proteins were retrieved in batches from the UniProtKB database (Release 2013_12) in FASTA format. The retrieved sequences were locally searched against the SwissProt database (human) using the NCBI BLASTϩ client software (ncbiblast-2.2.28ϩ-win32.exe) to find homolog sequences so that the identified sequences can be functionally annotated. The top 10 blast hits with an E-value less than 1e-3 for each query sequence were retrieved and loaded into Blast2GO (16) (Version 2.7.0) for gene ontology (GO) (17) mapping and annotation. An annotation configuration with an E-value filter of 1e-6, default gradual enzyme codes (EC) weights, a GO weight of 5, and an annotation cutoff of 90 were chosen. Unannotated sequences were then reannotated with more permissive parameters. Sequences without BLAST hits and unannotated sequences were then selected for InterProScan (18) against EBI databases to retrieve functional annotations of protein motifs and merge the InterProScan GO terms to the annotation set. Following annotation and annotation augmentation steps, the studied proteins were blasted against KEGG genes (human) to retrieve their KEGG orthology identifications and were subsequently mapped to pathways in KEGG (19).
Immunohistochemistry-Formalin-fixed paraffin-embedded SPTP tissues (n ϭ 20) and matched normal pancreas tissue (n ϭ 20) were used for the IHC studies(see supplemental Table S3). All samples were obtained from the patients with informed consent and with approval of the institutional ethics committee. The following primary antibodies were used: anti-MSI2 rabbit affinity isolated, 1:200; anti-DKK4 rabbit polyclonal, 1:200; anti-JUP mouse clone 2G9, 1:150; anti-ACADL rabbit affinity isolated, 1:100; anti-EPHX2 rabbit affinity isolated, 1:100; and anti-DAD1 rabbit affinity isolated, 1:200. All antibodies above were obtained from Sigma-Aldrich and diluted in 0.1 M PBS. Anti-TRAM1 rabbit polyclonal, 1:100; anti-SEC61B rabbit poly-  and anti-ERO1LB rabbit polyclonal, 1:100. All antibodies above were obtained from LifeSpan Biosciences (Seattle, WA) and diluted in 0.1 M PBS. After deparaffinization and rehydration, antigen retrieval was performed by immersing the slides in antigen retrieval buffer (10 mM sodium citrate, pH 6.0) at 95°C for 30 min then treating with Tris-buffered saline with 0.1% Triton X-100 (TBST, pH 7.6) for 5 min. Endogenous peroxidases were blocked with 3% hydrogen peroxide for 10 min. After washing three times with 0.01 M PBS, nonspecific binding was blocked with goat serum for 30 min. Tissues were then incubated with primary antibodies at 4°C overnight followed by incubation with peroxidase-labeled polymer conjugate to anti-rabbit immunoglobulins (Invitrogen, Carlsbad, CA) for 1 h at 37°C. After washing with 0.01 M PBS, DAB (Boster, Wuhan, China) was used to visualize tissue antigens. The sections were counterstained with hematoxylin and dehydrated. All slides were examined and scored by two of the pathologists who were blinded to clinical data of patients. Staining intensity was recorded on the following scale: 0, no staining was observed, or staining was observed in less than 10% of tumor cells; 1ϩ, mild perceptible staining was detected in more than 10% of tumor cells; 2ϩ, moderate staining was observed in more than 10% of tumor cells or strong staining in less than 30%; and 3ϩ, strong staining was observed in more than 30% of tumor cells.
Statistical Method-The statistical differences in IHC scores of tumor tissues and matched adjacent non-tumor tissues were analyzed by a paired t test. p Ͻ 0.05 was considered to indicate a statistically significant difference. Statistical analysis was performed using the Statistical Program for Social Sciences (SPSS) software 17.0 (SPSS Inc., Chicago, IL).

RESULTS
To identify differentially expressed proteins in SPTP we performed a study based on the technology of LC-MS/MS combined with SCX. Equal amounts of proteins from normal pancreas and matched tumor specimens were digested by trypsin and the resulting peptide mixture was labeled using iTRAQ reagents (113 as an internal control; 114, 115, and 116 for the normal samples; 117, 118, and 119 for the SPTP specimens). The iTRAQ labeled peptides were fractionated by SCX chromatography and the eluted fractions were then analyzed by LC-MS/MS. The recognized peptides were then searched against the UniProt Knowledgebase (version: 2013.11). The whole workflow is shown in Fig. 1. A total of 26,209 peptides Supplemental table S6 matching 4507 proteins (Ն1 peptide) Supplemental table S7 were identified from the tissue analysis. Fold changes of proteins were determined by the ratios of the iTRAQ reporter ions between normal and tumor samples. Using a threshold of 1.5-fold change and a p value Յ0.05, 1171 proteins (558 up-regulated and 613 downregulated; see supplemental Table S2) were extracted. The top five up-regulated proteins in the proteomics analysis are hepatocyte growth factor-like protein alpha chain, gelsolin, hemoglobin alpha-2, doublecortin domain-containing protein 5, and hemoglobin beta chain. The top 5 down-regulated proteins are a-kinase anchor protein 11, zinc finger protein 714, hydrocephalus-inducing protein homolog, cytochrome c oxidase subunit 2, and trypsin-1.

FIG. 2. Immunohistochemistry of individual SPTP tissue and corresponding normal pancreas tissue from same patient (400x).
Up-regulation of MSI2 and DKK4 and down-regulation of JUP, ACADL, EPHX2, and DAD1 were confirmed in SPTP specimens. The IHC protocol is described in the Materials and Methods. The staining scoring details are shown in Table II.  3. Distribution of Gene Ontology (GO) functional categories in the SPTP proteome. Each annotated protein is assigned at least one GO term. All data are presented on the basis of GO second level terms. Numbers refer to assigned proteins in each category.
In order to confirm the mass spectrometry results, we selected six differentially expressed proteins (ACADL, EPHX2, JUP, MSI2, DKK4, and DAD1; see Table I) to be examined by IHC. We selected these six proteins because of 1) potential functional significance, 2) more than one peptide was identified by LC-MS/MS, and 3) a link to SPTP had not previously been reported. IHC was performed with 23 SPTP and five normal pancreas tissues. Representative IHC images were shown in Fig. 2, and the IHC results were summarized in Table  II. MSI2 was mainly expressed in the nucleus whereas the other five proteins were expressed in the cytosol. For the two up-regulated proteins, moderate to strong positive staining (Ͼ1ϩ) was shown for MSI2 in 75.0% of the SPTP cases (15/20)   negative to moderate staining (Յ1ϩ) for these four proteins was 10% (ACADL), 20% (EPHX2), 5% (JUP), and 15% (DAD1). Pairs t test showed a statistically significant differ-ence (p Ͻ 0.05) between the scores of the tumor-normal pairs for all these six proteins, which coincided with the MS findings. All the 1171 proteins identified by MS were subsequently classified by bioinformatics analysis. The gene ontology (GO) database is an internationally standardized gene functional classification system to comprehensively describe characteristics of different genes and their products. A total of 1078 proteins differentially expressed in SPTP were annotated to 10,824 GO function entries. Second-level GO terms were applied to classify proteins in terms of their involvement in three main categories (biological process, cellular component, and molecular function) and each protein was assigned at least one term. More than 75% (927 proteins) were annotated as belonging to the cell compartment, and the other two main categories of these proteins were the membrane (402 proteins) and organelle (716 proteins) compartments. As summarized in Fig. 3 and supplemental Table S4, the top three molecular functions were protein binding (737 proteins), catalytic activity (332 proteins), and enzyme regulatory activity (46 proteins). The top three biological processes identified were cellular process (972 proteins), single-organism process (849 proteins), and metabolic process (804 proteins).
Because different proteins interact and cooperate to complete biochemical reactions, a KEGG pathway-based analysis was performed to identify pathways that would be potentially affected by differential protein expression in SPTP. The top three pathways identified were the ribosome (81 proteins, p Ͻ 0.01), protein processing in the endoplasmic reticulum (42 proteins, p ϭ 0.01), and the complement and coagulation cascades (30 proteins, p Ͻ 0.01) (Fig. 4 and Table III). All KEGG analysis results are shown in supplemental Table S5. Several important proteins, such as protein disulfide-isomerases and protein transporter protein SECs, with functions in protein export, protein degradation, or ribosome anchoring could be classified as part of the endoplasmic reticulum protein processing pathway (Table IV). The expression of majority of these proteins was significantly reduced in SPTP tissues compared with the normal tissues.
Next, seven markers (ERO1LB, TRIM1, GRP94, BIP, SEC61B, P4HB, and PDIA4) associated with the endoplasmic reticulum protein processing pathway were selected for validation of post-proteome bioinformatics by IHC in 20 normaltumor pairs. We selected these seven markers because of the different functions in this pathway and significant foldchanges. Except SEC61B, all the other six markers showed a higher IHC staining scores (p value Ͻ0.05) in normal pancre- FIG. 5. Immunohistochemistry image for markers associated with endoplasmic reticulum protein processing pathway in individual SPTP tissue and corresponding normal pancreas tissue from same patient (400x). ERO1LB, TRIM1, GRP94, BIP, SEC61B, P4HB, and PDIA4 were confirmed in SPTP specimens. The IHC protocol is described in the Materials and Methods. The staining scoring details are shown in Table V. atic tissues compared with the marched tumor tissues (Table  V and Fig. 5). These markers, together with DAD1 indicated that abnormal expression of many proteins belonged to this pathway existed in SPTP.

DISCUSSION
Researchers have not paid much attention to SPTP because it is a rare disease with a favorable prognosis. The proteomic data presented in this study and validated by IHC is to our knowledge the first report of a differentially expressed proteome in human SPTP. These data not only provide confirmation of earlier studies but also reveal new information about SPTP, which will facilitate further investigation of the disease.
Consistent with previous studies suggesting that cell adhesion or cell junction abnormalities are one of the most important pathogenic factors of this disease, many proteins associated with those functions were found in our data. For example, the claudin family plays an important role in cellular tight junctions. Immunohistochemical analysis of claudin expression levels in SPTP specimens showed intense membrane staining of claudin and cytoplasmic staining of claudin 2, lack of claudins 3 and 4, and positive staining of claudins 1 and 7 in several specimens (20 -21), which corresponds with our results. CD99 has also been identified as a specific pathological biomarker for SPTP because of its paranuclear dotlike staining pattern (11,12,22). We also found that the expression level of CD99 in SPTP is lower than it is in the normal pancreas. More proteins identified as differentially expressed that are associated with cell adhesion such as F11 receptor (JAM1) and junction plakoglobin (JUP) are shown in Table VI and could be further investigated as pathologic biomarkers or pathogenic factors.
The top three pathways identified from the KEGG database analysis were the ribosome, protein processing in the endoplasmic reticulum, and the complement and coagulation cascades. To date, many studies have shown that the reduction of specific ribosome protein subunits might cause severe diseases (23)(24). Our results show that almost all subunits of the 60S and 40S ribosomal proteins are reduced in the SPTP specimens, suggesting that protein biosynthesis may be attenuated at a global level. In addition, we found that the expression of a large number of proteins participating in the endoplasmic reticulum protein processing pathway was aberrant in this disease.
The endoplasmic reticulum (ER) is a cytoplasmic organelle in which secretory or membrane proteins are synthesized. Briefly, ER stress is defined as an imbalance between the protein folding capacity of the ER and the protein load, resulting in the accumulation of misfolded proteins (25). ER stress has been speculated to be involved in most conformational diseases, such as Alzheimer's disease and Parkinson's disease and some of the specific pathogenic unfolding proteins have also been identified (26 -27). Based on our findings, we speculate that the whole ER protein processing pathway might be disrupted in SPTP because of abnormal expression of ER-associated proteins Fig. 6. ER chaperones consist of molecular chaperones and folding enzymes located in the ER, whose responsibility is the folding of nascent proteins (28). Binding protein (BIP), which belongs to the HSP70 family, is a core molecular chaperone that binds to the hydrophobic region of unfolded proteins and facilitates folding (29). Other molecular chaperones, such as SEC63 and DNAJC3 have been identified as cochaperones that modulate the function of BIP, were also reduced in SPTP tissues in our study. Furthermore, we found numerous folding enzymes, such as protein disulfide isomerases (PDI) and dolichyl-diphosphooligosaccharide protein glycosyltransferase (OST), were down-regulated in the SPTP specimens. These folding enzymes coordinate to oxidize cysteine residues of nascent proteins and help proteins to form correct disulfide bonds. Reduced folding enzymes are reoxidized by ER oxidoreductin (ERO1) (30), which was also down-regulated. Additionally, the abnormal expression of osteosarcoma 9 (OS9) and XTP3-transactivated gene B (XTP3B), which are ER-associated degradation (ERAD) components responsible for the recognition of unfolded proteins (31)(32)(33), occurs in SPTP compared with normal pancreas. Together, our findings suggest that the aberrant expression pattern of these proteins may cooperate to cause the accumulation of some misfolded proteins in the ER, which may endow the disease with a "degenerative property." Additionally, Kim and col-leagues have suggested that the nuclear pleomorphism of SPTP is a degenerative change rather than an alteration with high-grade malignant potential because of a lack of mitosis and low K i -67 labeling index (34).The subsets of proteins from this and other altered pathways could be further investigated first for technical validation and then for clinical applications.
In conclusion, our study is the first systematic proteomic analysis of SPTP. Generating a high-confidence list of differentially expressed proteins in rare tumors is important to both doctors and patients. The relationship between ER stress and SPTP tumorigenesis has not been previously recognized, and suggests that future studies should be aimed at identifying pathogenic unfolded proteins in this disease. □ S This article contains supplemental Tables S1 to S7. ¶ To whom correspondence should be addressed: Department of Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, P.R. China. Tel.: 86-21 64370045; E-mail: haochendr@126.com and chhpeng@188.com.
ʈ These authors contributed equally to this work.
FIG. 6. Putative endoplasmic reticulum protein processing pathway. A putative endoplasmic reticulum protein processing pathway was constructed based on KEGG mapping. Green squares indicate proteins identified as differentially expressed proteins; white circles indicate proteins not identified as differentially expressed in our study.


extfieldsofstudy: Chemistry Medicine

text:
Shedding Light on Protein Folding, Structural and Functional Dynamics by Single Molecule Studies

The advent of advanced single molecule measurements unveiled a great wealth of dynamic information revolutionizing our understanding of protein dynamics and behavior in ways unattainable by conventional bulk assays. Equipped with the ability to record distribution of behaviors rather than the mean property of a population, single molecule measurements offer observation and quantification of the abundance, lifetime and function of multiple protein states. They also permit the direct observation of the transient and rarely populated intermediates in the energy landscape that are typically averaged out in non-synchronized ensemble measurements. Single molecule studies have thus provided novel insights about how the dynamic sampling of the free energy landscape dictates all aspects of protein behavior; from its folding to function. Here we will survey some of the state of the art contributions in deciphering mechanisms that underlie protein folding, structural and functional dynamics by single molecule fluorescence microscopy techniques. We will discuss a few selected examples highlighting the power of the emerging techniques and finally discuss the future improvements and directions.

Introduction
The arrival of single molecule (SM) techniques to study protein behavior in the last 50 years has unveiled a great wealth of dynamic information-unattainable by conventional averaging biochemical measurements-and provided new insights in the complex tapestry of protein dynamics, function [1][2][3][4][5][6][7][8] and regulation [9]. Single molecule studies offer the direct observation of heterogeneities rather than the average biophysical property from which they can be inferred [10][11][12][13][14][15]. By doing so they offer a unique set of properties all of which remain masked in classical biochemical assays due to averaging of a large number of unsynchronized molecules; firstly they provide the complete distribution of behaviors of the molecular entities in a population, as opposed to only their average behavior. Secondly they allow direct observation of transient intermediates and rare sampled states that remain masked in conventional ensemble kinetics. Thirdly they discriminate static and dynamic heterogeneities within a population. SM measurements have thus unveiled the existence of multiple, and in some cases rarely sampled, functional states [11,[16][17][18][19] confirming that proteins do not necessarily reside in the minimum energy of the ground states but may continuously explore the energy landscape while maintaining a native structure, and provided clues on how the sampling of a dynamic spectrum of functional states underlies signaling emergence [20]. Importantly SM studies provide evidence for the anticipated correlations [21,22] of the shape of the rugged energy landscape to all aspects of proteins, from folding to dynamics and function.
Single molecule studies have thus evolved from the initial proof of concept experiments to a guiding principle addressing the needs-and often resolving disputed mechanisms-of biological sciences. The two principal approaches [7,23,24] for observing single molecules rely on micromechanical manipulations and fluorescence spectroscopy and recently their combination [25]. Micromechanical manipulation involves optical and magnetic tweezers [26][27][28][29] as well as atomic force microscopy [30][31][32][33][34], while fluorescence measurements involves polarization, lifetime, particle tracking [3,[35][36][37], FRET [7,38] and intensity measurement [7,24,[39][40][41][42][43]. Realizing that SM studies has extended to practically all fields of modern biology, furnishing a detailed description of all single molecule results seems rather arduous, so here we shall confine ourselves to a unique set of single molecule methodology, that of fluorescence spectroscopy and the contributions it has made in deciphering mechanisms that underlie protein folding, structural and functional dynamics. This review is organized as follows. We will start with a short description of methodologies to observe protein dynamics. We will then discuss some daunting questions and insights attained by the emerging single molecule techniques on the dynamics that define the folding of biomolecules and underlie their function. The next section focuses on the SM insights on functional dynamics of enzymes. This will be followed up by our concluding remarks and a listing of potentially interesting aspects to watch for in the future.

Methods to Directly Observe Protein Dynamics of Protein Folding and Conformational Sampling
Deciphering the dynamics of protein that underlie its folding and function has been a central interest of multiple scientific groups [13,[44][45][46][47]. The key methods developed for that are Fluorescence Resonance Energy Transfer (FRET) and fluorescence quenching, and have been reviewed elsewhere [1, 5,6]. FRET was first used by Stryer and Haugland as a spectrometric ruler to probe distance information [48]. FRET involves a non-radiative transfer of energy from an excited donor fluorophore to a nearby acceptor fluorophore with overlapping spectra and optimal orientation of their transition dipoles. This causes a decrease in the donor fluorescence emission while increasing the fluorescence of the acceptor. The efficiency of the energy transfer (E) can be obtained by determining the ratio of acceptor intensity to total emission intensity. Forster provided the relationship between the energy transfer rate and the donor acceptor distance as E = 1/(1 + (R/R0) 6 ), where R is the inter-dye distance, and R0 is the Förster radius at which E = 50%, see Figure 1. Recording FRET changes at the single molecule level allows observations of conformational fluctuations that occur within the temporal resolution of the instrumentation setup-usually microseconds to seconds. The donor fluorophore when excited with laser either fluoresces or transfers a part of its energy to an acceptor fluorophore, depending on their distance. At distance equal to the Förster radius R = R0, E = 0.5. FRET changes are higher at distance variations around the Förster radius; (C) Typical time trace of single molecules (here DNA molecules) undergoing conformational fluctuations between two states recorded by fluorescence microscopy. Top trace shows the anticorrelated time traces of donor (green) and acceptor (red) molecules. Bottom trace shows the corresponding EFRET. ( Figure 1C adapted with permission from [47].) Single Molecule FRET (smFRET) is carried out primarily in a confocal or wide field microscopy setup [23]. In the confocal microscope, a laser beam is focused on a diffraction limited spot by a high numerical aperture objective lens. A high signal-to-noise ratio is achieved by the insertion of pinholes in the excitation path and in front of the detector, which allow point illumination and block the out-of-focus light respectively. As very low concentrations of fluorescently labeled samples are utilized, single molecules diffusing in the confocal volume can be resolved. Confocal setups are ideal for detection of both freely diffusing and surface immobilized molecules. Using fast and sensitive point detectors such as Avalanche photodiodes (APD) provides up to picosecond time resolution, albeit in a sequential manner hence increasing acquisition time and providing low throughput. Total Internal Reflection microscopy (TIRF) is the workhorse for wide field detection method. It is based on the phenomenon of total internal reflection which generates an evanescent field near the surface ( 100 nm). The exponential decay of the field intensity with increasing distance from the glass-water interface results in selective sample illumination and low background signal. Appended to a Charged Coupled Device (CCD) camera, allows parallel detection of several immobilized molecules providing adequate statistics, however with a lower temporal resolution in the submillisecond range.
smFRET is undoubtedly the most general and adaptable among many single molecule fluorescence techniques for biology and is ideally suited to directly record real time distance fluctuations in the range of 2-8 nm. It is however insensitive to shorter ranges of fluctuations that often occur in proteins and are physiologically significant. Recent developments allowed for the first time the observation of conformational dynamics with subnanometer sensitivity. Utilizing single molecule self-quenching of tetramethylrhodamines by the group of Taekjip Ha probed the 0.5 nm conformational motions of an ADP-sensing protein [49].
The techniques discussed above offer an indispensable view of proteins; from directly witnessing and deciphering the mechanisms of folding of proteins to their native state(s) to the observation of conformational dynamics that underlie function. Selected publications and reviews are discussed below.

Single Molecule Insights into Protein Folding Mechanisms
Understanding how the primary amino sequence of the polypeptide chain dictates a unique native structure and the nature of folding pathway that leads to it, has eluded scientists for over 50 years [21,[50][51][52][53]. The classical theory of protein folding posits a smooth, deterministic folding pathway having a discrete number of intermediate structures [54,55]. The currently most convincing model of protein folding is that of the "folding funnel" based on the concept of energy landscape. The energy landscape defines the thermodynamic and kinetic parameters that underlie the relative distribution of the conformational states and the energy barriers separating them respectively [56,57]. The folding "funnel" is proposed to be rugged, over which a polypeptide could follow multiple pathways and stochastically sample a plethora of intermediates that funnel the molecular fluctuations en route to the native state [53,58,59]. The existence of multiple pathways and the conformational sampling of transient intermediates can be described by theoretical models of protein folding and computer simulations but is masked in conventional measurements that report the average property of a large ensemble of unsynchronized molecules. Single molecule studies with the advantage of directly probing multiple subpopulations and stochastic dynamics in a heterogeneous ensemble are emerging as new and powerful tools in deciphering the mechanism of these complex processes. Protein folding insights obtained by single molecule studies have been extensively reviewed elsewhere [1, [60][61][62][63]. A few selected examples shall be discussed in the following section.
Pioneering SM fluorescence-based studies on protein unfolding were performed on dual labeled, freely diffusing molecules in equilibrium conditions. Deniz et al. utilized smFRET to characterize the unfolding of Chymotrypsin Inhibitor (CI2) under equilibrium conditions [64]. A TMR/Cy5 labeled CI2 was subjected to different concentrations of the denaturant guanidinium chloride and analyzed by FCS allowed the observation of the existence of two populations-folded and unfolded-and how their relative distributions are altered by different denaturant concentrations and more importantly by destabilizing mutations. FRET efficiency histograms revealed that at close to native (low) concentrations of GdmCl, CI2 appeared as a single predominantly folded species with a high FRET efficiency. Increasing the denaturant concentration to intermediate levels split the unimodal FRET distribution to having a second off-peak with low FRET efficiency indicating the equilibrium between the folded and unfolded states. When increasing further the GdmCl concentration the high FRET peak disappeared, which indicated the collapse of the ordered conformation to an unfolded one. This confirmed the presence of a simple two state folding pathway for CI2, previously suggested by bulk studies. Similarly, a two-state folding pathway was observed for the cold shock protein from the bacterium Thermotoga maritima (CspTm) [65] and RNase H [66] by SM measurements in equilibrium conditions. Interestingly, a combination of smFRET and NMR approach on the gradual unfolding of a slow two state folder SH3, suggests that folding mechanisms under biological conditions could differ from those deduced by experiments conducted in denaturing conditions due to plasticity of the folding landscapes [67].
Protein unfolding studies conducted under freely diffusing conditions could mask the existence of subpopulations that are sparsely populated at equilibrium. To observe folding kinetics under non-equilibrium conditions and study the possible existence of subpopulations in the folding of CspTm Lipman et al. [68] employed a microfluidic laminar flow mixer device [69] coupled to a confocal microscope. While diffusing through the confocal volume proteins were subjected to an abrupt reduction in denaturant concentration that favored the folded state. However, they identified only two major conformations, confirming earlier studies. Recently a low-cost microfluidic mixing device based on hydrodynamic focusing and diffusing mixing has been developed by the group of Schuler [70]. Using this setup they measured smFRET on unfolding of the B-domain of protein A and the conformational dynamics of the pore forming toxin ClyA, by mixing of the denaturant GdmCl and detergent n-dodecyl-β-D-maltopyranoside (DDM), respectively. This setup offers measurement of single molecule kinetics at the timescales of milliseconds to minutes.
In order to attain long trajectories of individual molecule and obtain ample data for statistical analysis, immobilization strategies were invoked. However, direct immobilizing proteins on surface may induce non-native surface interactions that may interfere with single molecule studies [2,71,72]. Seminal work on employing star-shaped polymers to minimize non-specific interactions with the glass surface showed that proper surface passivation may not affect dynamics [66]. This paved the way for the wide implementation of passivated surfaces with PEG polymers and the use of biotin-avidin interaction to immobilize biomolecules. Lately a very promising immobilization strategy has been developed which involves encapsulation of proteins in lipid vesicles that are tethered on the microscope slide surface via e.g., avidin biotin interactions, see Figure 2A. This approach allows spatial localization of protein under investigation minimizing interactions with non-native environment. Utilizing this technique for unfolding studies on adenylate kinase (AK), led to the observation of multiple folding pathways and the existence of multiple, small partial folding/unfolding jumps. This indicated the presence of small local traps on the rugged free energy landscape [73]. This strategy was further exploited by Pirchi et al. [74] which has identified the existence of six metastable states in the multidimensional folding landscape of AK. Using a large number of equilibrium smFRET trajectories of AK they have directly observed the pathway that connects these states and its rerouting by changes in denaturant concentration. They also recorded the rates of their interconversion in the folding process as shown in Figure 2B. These data allowed sketching of a multiple state energy landscape, while hinting towards a "foldon" hypothesis [75]. In the quest of attaining information on distribution of folding pathways, the group of Eaton has employed a single molecular FRET approach to determine the average transition path times of a fast and slow folding protein [76] as well as the dynamics of barrier crossing [45]. They demonstrated that despite a 10,000-fold difference in their folding rate coefficients, the transition path times differ only by a factor of five. Hence the slow and the fast folding proteins would take almost approximately similar time to fold when the folding process would occur [76].
Single molecule studies have recently expanded in dissecting the mechanism of folding and function of Intrinsically Disordered Proteins (IDP). IDPs lack, partially or completely, an ordered 3D structure and are involved in a spectrum of diseased states such as cancer, cardiovascular and neurodegenerative disorders and diabetes [77][78][79]. While their inherent dynamic nature is challenging to be studied by conventional bulk methods the ability of SM methods to directly detect and quantify fleeting intermediates has an especially important take-away in IDP. The greatest advantage of SM has been in investigating amyloidogenic IDPs where the low protein concentration requirement of the SM studies minimizes the formation of higher order oligomers and allows studies of the folding intermediates. smFRET studies have been extensively employed for deciphering the folding mechanisms and conformational sampling of multiple IDPs such as the NM-region of the yeast prion protein Sup 35 [80], α-Synuclein [81][82][83][84], islet amyloid polypeptide (IAPP) [85] and Tau proteins [86]. These studies have highlighted the role of environmental conditions such as presence of denaturants, membranes or osmolytes on the structural fluctuations and dynamics in IDPs. In addition, manifestation of allostery has been demonstrated in a molecular hub IDP, the adenovirus early region 1A (E1A) oncoprotein [87]. Similarly the group of Schuler has investigated the effects of temperature, pH and crowding agents on the conformational collapse of unfolded proteins and IDPs [46,88,89]. Using a combination of smFRET, theory and simulations they provided new, often unexpected, insights on the collapsing protein behavior. Their studies showed that the temperature-induced collapse is a common feature of multiple IDPs with different sequences [89]. They furthermore revealed that in addition to hydrophobic effects, the temperature-dependent solvation free energies of the relevant amino acids have a dominant contribution in the collapse. Similarly their studies in the presence of crowders revealed IDP compaction to depend not only on the concentrations but also on the size of the crowder [46]. This unexpected behavior, based on the theory from scaled-particle, was explained quantitatively by taking into account the polymeric nature of the crowder and the protein. A very recent and exhaustive review enlisting the wealth of work on the application of single molecule studies to IDPs has been published [90]. Probably the most exploited field by smFRET involves measurements of conformational dynamics of folded proteins and biomolecules. In the next section, we will focus on how SM measurements could decipher the highly debated role of conformational motions to the catalysis step.

Single Molecule Insights into the Role of Protein Conformational Dynamics to Function
Proteins are conformationally inhomogeneous and inherently dynamic; a phenotype that stems from the stochastic search of intermediates during folding and extends to the sampling of the conformational space in the native state. Several review papers addressing this fundamental attribute of proteins have been published [21,22,91,92]. While it is in general well appreciated that these dynamics and exploration of the conformational space are important attributes of protein function, deciphering how exactly these dynamics control protein function has eluded scientists for over 30 years [93] and has been the central quest of multiple research groups [91,[94][95][96][97]. In fact, it is currently being disputed whether protein dynamics do catalyze the chemical step [98]. Single molecule structural studies are becoming an indispensable tool in the quest of decrypting the potential role of protein dynamics in function. In this section, after briefly outlining the current debate on the direct coupling of conformational dynamics to the catalysis step, we will show how emerging single molecule techniques could potentially provide solutions to this debate by directly and synchronously recordings of protein conformation and function. In Section 2.2 we will discuss the only methods to directly observe individual catalytic cycles but not the conformational dynamics that potentially underlie them.
Pivotal work from the group of Kern aimed to realize if enzyme conformational motions are random or pre-encoded to follow a pathway optimized for the chemical step [99]. They utilized adenylate kinase which has two "substrate lids" that within the catalytic cycle undergo a transition from the open to the close conformations. Combining smFRET readout with dynamic simulation and NMR studies revealed that AK exists in equilibrium between an open and closed state. Importantly they directly observed protein conformational motions to occur in similar time scales with the catalysis step, as calculated by ensemble averaging kinetic measurements. Their data suggested that protein motions are not random but deterministic and directed by the energy landscape; the fast time scale (picoseconds to nanoseconds) hinge domain motions collectively drive the slow large domain motions (microseconds to milliseconds) that are anticipated to be catalytically important. They thus proposed that the hierarchy of protein dynamics in space and time arises from the protein structure encoded by the amino-acid sequence and is ultimately connected to enzyme function. This claim however; of the direct coupling between conformational dynamics and chemical kinetics is now being heavily challenged [100,101]. Deciphering such conundrums may require direct and synchronous observation both conformational motions and function that to date can only be attained by single molecule studies.
The group of Kim recently attained the direct and synchronous observation of protein conformational dynamics and function of an individual maltose binding protein (MBP) [102]. To do this they performed three-color FRET, by combining a Cy3/Cy5 FRET pair labeled MBP and fluorescently Cy7 tagged ligands as shown in Figure 3. Their results reveled that although capable of binding to both closed and open forms, ligands preferentially interact (>75%) with the closed state and that ligand binding also altered primarily the closing rates of MBP, directly observing for the first time, how structure of the protein controls its function. Later studies revealed that intrinsic opening rates also control ligand dissociation and hence binding affinity of MBP [103]. Their single molecule readout also deciphered whether the mechanism of underlying ligand recognition operates via the "Induced fit" or the "conformational selection" model [9,92].

Methods to Attain Single Molecule Insights in Protein Functional Dynamics
Single molecule functional studies have revolutionized our understanding of how enzymes work. The journey from Rotman's first attempts [104] to date has been remarkable, with the development and implementation of several methodologies to monitor the activity of individual enzyme molecules. Single particle tracking studies were used to correlate distance information to enzymatic activity and reveal the underlying mechanisms for several enzymes such as kinesin [12], dynein [105] and phospholipases [106,107]. The workhorse of single molecule fluorescence functional assays is a "tag" capable of demonstrating fluctuations in its own fluorescence to resolve the individual catalytic cycles of an enzyme.
The initial single turnover resolution experiments utilized the intrinsic fluorescence properties of the flavin cofactors of enzymes [11,108,109], see Figure 4A. As these flavin cofactors cycle between their fluorescent oxidized ("on") state and non-fluorescent reduced state ("off"), they provide real time information of individual stochastic catalytic cycles. The greatest advantage of this approach was the absence of mutagenesis and site specific labeling while its inherent limitation was the low quantum yield of the cofactors and their tendency to dissociate and bleach limiting the fluorescent trajectories to a few turnovers. Such limitations were surpassed by employing the redox state dependent quenching of a biochemically attached photostable fluorophore on Nitrite reductase from Aspergillus niger [110,111]. Within each turnover cycle its copper cofactor sequentially transits from a reduced to the oxidized which in turn efficiently quenches the site-specifically attached fluorophore. However, the credit of revolutionizing single molecule functional assays goes to prefluorescent substrate analogues, which discarded the pre-requisite for enzymes to have fluorescent cofactors or undergo significant structural transitions in order to record functional cycles, see Figure 4B. In this approach, non-fluorescent substrate analogues upon enzymatic reaction are converted to highly fluorescent products generating the stochastic single molecule fluorescence (SMF) trajectories like the one shown in Figure 4C. The superiority of this technique lies in overcoming the issue of photo bleaching, allowing observation of large number of turnovers limited only by substrate depletion, significantly improving statistical analysis. This platform has been applied to a broad and diverse class of enzymes ranging from β-galactosidase [112] to lipases from Candida antarctica (CALB) [19], Thermomyces lanuginosa (TLL) [17,113], proteases like chymotrypsin [114], and oxidoreductases like Horse radish peroxidase [115] and P450 Oxidoreductase (POR) [16].
Single turnover resolution measurements revealed previously masked (a) time dependent activity fluctuations for enzymes and (b) heterogeneities in activity between seemingly identical enzymes of a population. The observation of the existence of these heterogeneities, have been discussed earlier [39,116]. Here we will provide latest insights and attempts to provide explanations of the mechanistic origin of these heterogeneities. Some of the wide implications of these heterogeneities will then be discussed. Dynamic disorder is the time-dependent activity fluctuations of an enzyme. Initially dynamic disorder was proposed to originate from the existence of a continuous distribution of protein states with different activities, a phenotype that was anticipated to pertain to the majority of enzymes. Latest studies however provided evidence that a limited number of discrete functional states may equally well describe the behavior of multiple enzymes. Here we will outline these studies and their insights. The first direct observation of dynamic disorder was presented by the group of Xie on molecules of cholesterol oxidase by monitoring fluorescence fluctuations of its FAD cofactors [11]. Enzymes were spatially confined in a porous agarose gel which allowed free exchange of its substrates and products. Statistical treatment of SMF trajectories yielded waiting time histograms and autocorrelation functions, which did not fit with a monoexponential function indicating time dependent activity fluctuations. While the activity fluctuations could be fit with a model of two activity states the authors proposed the existence of multiple protein states. Ever since, time dependent activity fluctuation of individual molecules has been found to be representative for most water soluble enzymes studied up till date such as Horse Radish Peroxidase [115], Lipases from Candida antarctica (CALB) [19] and Thermomyces lanuginosua (TLL) [17,113], β-galactosidase from E. coli [112], nitrite reductase [110,111], dihydroorate dehydrogenase [72], hydroxybenzoate hydroxylase [108], and P450 oxidoreductase [16].
We recently extended the observations of dynamic heterogeneities and identified for the first time the existence of discrete functional states that are linked to the enzyme's conformational states [17].
Using arrays of surface tethered liposomes [117][118][119][120][121][122][123][124][125] we investigated the activity and regulation of a membrane related enzyme, the lipase. Lipases are enzymes that catalyze the enantioselective hydrolysis of esters in solution [126][127][128][129][130] with attractive biotechnological applications [131,132]. TLL is a typical interfacial activated lipase model system that shows low or no activity in solution but in the presence of an interface i.e., membranes the peptide-lid that otherwise blocks its active site is displaced, rendering TLL catalytically active [133]. We tethered TLL on surface immobilized liposomes by a flexible linker and interrogated its activity on prefluorescent substrate analogues by titrating in a progressive and quantitative manner its proximity to its effector, the lipid membrane. Our findings revealed TLL to oscillate between two functional states a highly active one and a practically inactive one. Importantly these functional states correlated with the enzyme major conformational states; the inactive state can be assigned to the closed lid conformation while the highly active state to the open lid conformation.
To investigate whether the existence of a discrete number of functional states pertains to transmembrane enzymes, we recorded the first single turnover measurement of a membrane-spanning enzyme P450 oxidoreductase (POR). To maintain POR in "native like membrane environment" we employed nanodiscs [134] to reconstitute P450 oxidoreductase (POR) [16]. POR is the obligatory electron donor to all microsomal P450s [135,136] and aberration in its function results in spectrum of diseased states ranging from cortisol deficiency to skeletal dysplasia [137][138][139]. A single cysteine POR variant labeled with Cy5 was reconstituted in DiO labeled Nanodiscs that were subsequently tethered on passivated surfaces, see Figure 5A. Using confocal fluorescence microscopy we recorded individual POR catalytic cycles on a prefluorescent substrate analogue resazurin. Our results revealed POR to sample to two major functional states, a highly active and a practically inactive one in agreement with our finding on TLL [2,9] (see Figure 5B). To date the existence of dynamic disorder is evident in most enzymes and is intuitively assumed to originate from the enzymes sampling of a spectrum of conformations, each of which has different activity. Proteins are indeed highly dynamic exploring the conformational space and sampling conformations in time scales that range from ps to ms or longer [91,92,[140][141][142][143]. The initial single molecule functional studies revealed time dependent activity fluctuations in the same time scale as slow protein conformational motions. It was thus intuitively assumed that these activity fluctuations stemmed from protein conformational fluctuations. In fact even though the activity fluctuations of the pivotal studies on cholesterol oxidase and dihydropholate reductase were sufficiently interpreted by models with two functional states [11,[144][145][146] more complex behavior was assumed and multiple activity states models were used [144,145]. This phenotype was adopted by a variety of other single molecule studies proposing enzyme to sample a spectrum of conformational states each with its own activity [23,39,40,116,147].
Increasing evidences support that simpler models with a discrete number of functional states may adequately describe the behavior of enzymes [17,146,[148][149][150][151]. Our recent results supported this emerging notion by showing that multiple-though not all-enzymes sample two rather than multiple functional states. We recorded the activity two lipases [17], (one from Candida antarctica and the other from Thermomyces lanuginosua) and POR [16]. We also retreated published data for the nitrite reductase from Alcaligenes faecalis [111], bovine α-chymotrypsin [114], and β-galactosidase from E. coli [112] in a way covering most of the enzymes where single turnover resolution measurements with high statistics is available. The tetrameric β-galactosidase as expected exhibited more complex behavior. Importantly we found that the behavior of the lipases, nitrite reductase and POR-four out of the five monomeric enzymes-was accurately described by two rather than multiple functional states. The existence of a small number of discrete functional states was also directly observed by pioneer single molecule measurements on lysozyme [148,152] further supporting this to be a generic phenotype underlying the behavior of multiple enzymes.
Along the same lines, recent work by Terentyeva et al. highlighted the possible limitations and artifacts that may arise from treating single turnover trajectories and questioned the existence of dynamic disorder for α-chymotrypsin, and possibly for other enzymes. Performing a systematic evaluation of commonly used binning and thresholding methodology of published data on α-chymotrypsin and simulated data they illustrated that the concave shape of the waiting time distribution-widely employed as a hallmark of distribution of functional states-may be due to artifactual data treatment [150,151]. They proposed change point analysis as a more accurate methodology to evaluate data and illustrated α-chymotrypsin to have a single activity over time rather than sampling multiple functional states. Their data signified the difficulties to accurately determine the number of exponentials underlying the waiting time histograms, if the number of exponentials needed for the fit is more than three. To resolve similar issues, Flomenbom et al., developed methodology for filtering noise using numerical algorithm that is based on a general likelihood function [153].
The existence of a discrete number of functional states does not repudiate the inherent protein dynamic behavior. Regulated proteins, ion channels and enzymes often oscillate between active and inactive conformations. Enzymes throughout the evolutionary course may have optimized what is needed for proficient regulation discarding unwanted functional states, maintaining few or two of them with large activity differences. The highly active states(s) of enzymes may emanate from optimized conformational coordinate and dynamics towards what is important for barrier crossing and catalysis [92,154,155]; any improper active site organization or dynamics relevant for catalysis would result on the practically inactive state(s). Importantly the existence of a small discrete number of functional states is in full agreement with the simple two-state models often employed by ensemble studies to describe regulated protein behavior [156,157], bridging ensemble with single molecule measurements.

Static Disorder: Multiple Distinct Folds of the Same Sequence or Chemical Heterogeneities?
Static disorder describes the heterogeneities of activity rates between individuals of a seemingly identical population. The path breaking work on single molecules by Rotman yielded the first hints for the existence of static heterogeneity by proposing that heat inactivation of enzymes occurred in an "all or none" manner [104]. However, it took 30 years of methodological improvement to attain direct observation of static disorder. Xue et al. reported up to a four-fold difference in the activities of individual lactate dehydrogenase enzymes lasting for a period of around 2 h [158]. However, the nature of origin of these functional differences has been debated ever since. The two opposing theories propose static heterogeneities to emerge either from chemical heterogeneity or presence of distinct, long lived conformational states. The latter could be a result of different folding patterns for different molecules whereby each could reside in different local minima separated by high energy barriers in the free energy landscape.
Chemical heterogeneities such as proteolytic damages and post translational modifications of the protein were proposed to underlie the observed static disorder in cholesterol oxidase [11] and alkaline phosphatase respectively [159]. The hypothesis of long lived conformational states related disorder was supported by the low throughput measurements on lactate dehydrogenase enzymes [158]. To scale up the number of molecules available for analysis the group of Walt et al. developed a high throughput assay utilizing femtoliter size reaction vessels that allowed the parallel readout of the activity of hundreds of individual enzymes [18,160]. The temporal resolution of a few to 10s of seconds averaged out millisecond activity fluctuations and allowed the observation of a broad distribution of activity rates. These were found to originate from a distribution in kcat rather than Km. The static heterogeneities were thus attributed to distinct long lived activities of the enzyme, however transitions between such long lived states were not directly observed. Later studies by the same group used short heat pulses to record switching of the β-galactosidases between long lived states of different activities [161]. The authors noted that only 25% of the β-galactosidase enzymes have identical amino acid sequences during the expression highlighting the contribution of chemical heterogeneities in static disorder. The heat dependent transitions between some of the protein states however support the existence of multiple thermodynamically trapped states with different activities in the protein energy landscape. Similarly smFRET measurements directly observed individual ribozymes to fold into multiple distinct native states with different activity [162]. Ribozymes were found to interconvert between these states in ultra-slow time scales (~9% of molecules in 40 min). It is thus becoming increasingly apparent that although some contribution from chemical heterogeneities may exist, static disorder may be a form of ultra-slow dynamic disorder. Static disorder may thus emerge from the inherent capacity of proteins to adopt multiple distinct folds and explore multiple energy minima in the free energy landscape separated by higher energy barriers.
The manifestation of multiple long lived states that extend into the realm of protein lifetime are expected to have mechanistic and biological significance since evolutionary pressure is required to evolve and maintain them [163]. Indeed recent pivotal work by the group of Gorris provided the first single molecule insights on the functional diversity of evolving enzymes [164]. Using arrays of femtoliter reaction chambers they compared the activity behavior of β-glucuronidase (GUS) and partially evolved GUS variants-called generalists-that retain their wild-type activity but also exhibit promiscuous activity accepting a broad range of other substrates. Their findings revealed significantly more broad long lived activity fluctuations for the partially evolved enzymes as compared to the wild type, see Figure 6. These data provided the first links of widths of activity distributions to increased variant promiscuity supporting the notion that increased widths of activity distributions-and thus functional promiscuity may serve as evolutionary starting points for the functional adaptation of enzymes [165].

Current Improvements and Future Directions
Great strides have been made in characterizing protein dynamics by single molecule fluorescence studies, however we are still at the tip of the iceberg and further improvements are required to keep in pace with their ever widening scope and applications of biology. There is a growing demand for a progressive evolution and combination of the presently available methodologies while simultaneously delivering novel solutions to combat limitations of the conventional techniques.
Attaining a comprehensive description of protein function in vivo requires implementation of powerful new technologies that combine single molecule readout in native-like conditions and parallel screening of biomolecular interactions. The development of high-density microarrays of biomimetic scaffolds such as liposomes [17,73,[118][119][120][121]166], nanodiscs [16,167,168] and polymer appended self-assembled nanostructures [169][170][171][172] for single molecule studies could be a novel way to implement screening of biochemical properties, molecular function or protein-effector and membrane interactions. Importantly it allows for the first time single molecule investigation of membrane spanning enzymes [16,117,167,173,174] in their native environment, the membrane. The massive parallel readout (10 3 -10 4 particles per frame) of such arrays could allow the direct observation of protein native states and quantification of their activity, abundance and importantly their dependence on regulatory inputs. Performing single molecule studies on crude cell extracts [175,176] is also bridging the gap between in vivo and in vitro platforms. As the native environment is preserved, it is possible to analyze in real time, the assembly, functioning and stoichiometry of macromolecular complexes. The development of methodologies like Photo Activation, Diffusion and Excitation (PhADE) [177] extends the useful concentration range for single molecule fluorescent imaging by at least two orders of magnitude and enables single molecule visualization at physiological concentrations.
A fundamental challenge of performing SM fluorescence experiments is site-specific coupling of the fluorophore (organic dyes, fluorescent proteins, quantum dots etc.) without perturbing the native structure and function of the host molecule. Although bioconjugation to specific thiols is the most efficient strategy, labeling of large proteins or those with high cysteine content could be difficult. Moreover, smFRET requires attachment of two fluorophores at specific positions. A possible solution to these is the use of bio-orthogonal chemistry [178,179] such as click chemistry [113,171,[180][181][182][183] to tag unnatural amino acids to provide a site specific and non-invasive labeling alternative. Utilization of recent advances of direct site specific bioorthogonal protein labeling in bacteria and cells is expected to improve single molecule studies in live cells [184][185][186].
Further, organic fluorophores are inherently labile and prone to reversible (blinking) or irreversible (bleaching) deactivation that limits their utility and performance. Although oxygen scavengers and triplet state quenchers are routinely added to delay such photophysical phenomena [187] these are poorly soluble and could be potentially harmful to biomolecules and alter the properties of bilayers [188]. The group of Blanchard demonstrated enhanced photostability and reduced blinking of several cyanine dyes by proximal conjugation of "protective agents" such as cyclooctatetraene (COT), 4-nitrobenzyl alcohol (NBA) or Trolox. These "self-healing" dyes could enhance the performance of SMF assays by providing a stable and robust reporter system, extending the observation regime to shorter time scales and potentially bridging gaps between experimental and computational methods [189][190][191]. Similarly Metal Enhanced Fluorescence (MEF), achieved by placing metal nanoparticles in close proximity to organic fluorophores offers enhanced fluorescence intensity and stability and has been successfully employed for single molecule FRET analysis of ribosomes [192]. Development of near infra-red fluorophores [193] and improving the properties of presently available quantum dots and fluorescent proteins will further expand the realm of SMF studies.
Utilizing emerging and currently existing SM techniques to measure structural dynamics will advance our understanding on the full fluctuation spectra of proteins and its interactions with partners. The established alternating-laser excitation (ALEX) methodology that simultaneously reports on structure, dynamics, and stoichiometries of fluorophores, by directly exciting the donor and the acceptor fluorophores of a FRET pair in an alternate fashion, is an invaluable tool in this quest [194,195]. Similarly the evolution of the conventional single pair FRET to multicolor FRET enables dissecting complex biological phenomena by allowing simultaneous observation of multiple parameters. Three and four color-FRET, combined with ALEX can evaluate three or six pairwise distances [196,197] allowing studies of dynamic multicomponent biomolecules. The group of Seidel recently developed a FRET-restrained high-precision structural modeling that explicitly accounts for the spatial distributions of dye positions and structural heterogeneity of biomolecules. This toolkit in addition to modeling the structure of proteins-here HIV transcriptase with DNA-allowed the observation of multiple biomolecular conformations in solution with ultrahigh temporal resolution [198]. It thus appears as exceptional toolkit for quantitative dynamics structural information of biomolecules. Lastly amalgamation of the two worlds of SM mechanical manipulation and fluorescence holds enormous potential to reveal the correlation between conformational dynamics and mechanical properties [199,200].
In this review, we highlighted some of the insights provided by single molecule techniques on protein folding, conformational dynamics and function that are currently being recognized as interdependent events perceptible by the protein's free energy landscape. The heights and the energy wells of the landscape define the pathway and energetics of folding to the native protein state while the amplitudes of the energy barrier and the thermodynamics between local minima dictate whether proteins rapidly interconvert between conformations or remain trapped in rarely sampled conformational and thus functional states. The existence of subpopulations of proteins with different functionality is anticipated to be crucial for cellular processes involving low copy numbers of proteins such as gene expression [201], signal initiation [20] phenotype switching [15] and even adaptive evolution [164] and is correlated to bacterial persistence to antibiotics [202]. Importantly, subpopulations might have subtle and yet significant differences in the affinities of their binding sites with regulatory cofactors and proteins partners that underlie their function and regulation. Single molecule functional and structural studies are ideally suited for directly observing their existence abundance and life times of these dynamics. Combining SM readouts with complementary interdisciplinary computational studies and spectrometric techniques such as NMR will enable bridging of multiple time scales and offer a holistic picture of protein dynamics and structure-function correlations. Integrating this knowledge into protein picture may contribute to the in silico design of novel pharmaceutics with increased efficiencies [203,204]. Similarly dynamic insights of both protein conformational ensembles, and the transition energy barriers could profoundly contribute in the "de novo" design of protein function [205,206] and engineering of enzymes with tailor made functionalities [131].


s2fieldsofstudy: Biology Medicine

text:
Counting CD4+ and CD8+ T cells in the spleen: a novel in vivo method for assessing biomaterial immunotoxicity

As immunotoxicity assessments of newly developed biomaterials are often restricted to use in assessment of local tissue response at the implantation site, they do not always show an immune response acceptable to qualify them for clinical use. We tested a new method to assess systemic toxicity: counting the CD4+ and CD8+ cells in the spleen. Three different biomaterials were subcutaneously implanted in three groups of rats for the same time period. After 31 days, their spleens were harvested, and CD4+ and CD8+ cells were counted. The mean CD4+/CD8+ cell counts were 24.5 ± 3.6/19.8 ± 4.0 (porous collagen matrix group), 25.5 ± 7.1/21.6 ± 3.8 [synthetic collagen matrix (Duragen®) group] and 28.1 ± 4.1/19.6 ± 3.7 (porcine dermis group). Differences in cell counts were not significant. The immunotoxic response generated against porous collagen matrix was comparable to that produced by a similar biomaterial already used clinically. This is, to the best of our knowledge, the first study on cytotoxic lymphocytes in the spleen to quantify systemic immune response to a biomaterial; however, such studies have been conducted with bacterial and viral antigens, and with vaccines. We believe that the present study provides a viable method for larger studies to confirm our current findings.

Introduction
Evaluating the reaction of the immune system with a foreign antigen is seemingly complex because the immune system that embraces various organs ranges from the peripherally located lymph nodes to the more centrally placed thymus and spleen, gut-associated lymphoid tissue, and interconnecting lymphatic and vascular channels. In addition, the antigenicity of the material being tested as well as its route of administration and dose affect local and systemic immune responses. It is essential to study the immune responses caused by implanting newly developed biomaterials in order to determine their safety for clinical use. Although national health regulatory organizations offer several guidelines for such tests, there are a few unequivocally sufficient and accurate methods for individual biomaterials. This is probably due to the complexity of immune system and the wide variety of new biomaterials being tested. Hence, a battery of tests must be considered for individual biomaterials to obtain an appropriate assessment of their immunotoxicity.
Immunotoxicity refers to any effect on the structure or function of the immune system, or on other systems as a result of immune system dysfunction. An effect is considered to be immunotoxic if it impairs the humoral or cellular immunity needed by the host to defend itself, or if it causes unnecessary tissue damage, such as autoimmunity, chronic inflammation or hypersensitivity. The immune system is adaptive and uses alternative mechanisms to compensate for particular deficiencies in function. This reason forms the basis for suggesting that using in vivo animal model tests rather than in vitro tests may provide a more accurate picture of immune competence and immunotoxic potential.
In vitro tests for cytotoxicity are usually elution tests which compare the effects of contact between monolayer cell cultures and controls with the tested materials. Although most of these studies have used fluid extracts from the experimental biomaterials, an appropriate in vivo assessment model is a crucial consideration in the safety evaluation of tissue-engineered products that may contain potential immunoreactive materials. Simple implant studies in which only local tissue reactions are evaluated are not considered systemic toxicity studies, regardless of how long the implants are in place. Immune responses to eliminate foreign particles involve cytotoxic T lymphocytes (CTLs) and non-specific cells such as natural killer (NK) cells and macrophages. Such kinds of effector mechanisms are directed at allogeneic cells, malignant cells, virus-infected cells and chemically conjugated cells. Immune activation of T cells results in a population of effector CTLs, which are often CD8 þ and, in rare instances, CD4 þ . Resting CTL or precursors, often referred to as CTL-P, are incapable of killing target cells until they are activated. For such activation to happen, a signal is provided when the T-cell receptor and CD8 cells on the CTL-P interact with an antigenic peptide class-I MHC (major histocompatibility complex) complex. A second signal, from cytokines, is induced by activated CD4 þ T cells. It may be generally assumed that cytokines produced by the activation of CD4 þ T cells are essential for a complete effector response from CTL. These CD4 þ T cells, often referred to as T H or T helper cells, are essential for generating CD8 þ T-cell-mediated target cell lysis. Hence, for a proper correlation of CD8 þ T-cell counts, a sufficiently large population of CD4 þ T cells appears necessary. Cytotoxic activity in the spleen has been reiterated by studies on the dynamics of cell activity in mice after a nearly total splenectomy [1]. Several studies have reported experimental evidence that T cells proliferate differentially in lymph nodes and the spleen [2][3][4]. A comparison of mice that were intravenously infected with vesicular stomatitis virus with mice that were orally given recombinant Listeria monocytogenes expressing ovalbumin (L. mOVA) showed that, with different antigens and different routes of administration, the activated CD8 þ cells were dissimilarly distributed in the lymphoreticular system [2]. The CD8 þ T-cell response in similar studies proved that secondary responses do occur in the spleen [3]. Experiments with influenza virus antigens showed that the proliferation of influenza-specific CD4 þ and CD8 þ T cells was predominantly found in the spleen [4].
Antigen-specific CD8 þ T-cell responses did occur in the spleen with the defined peptides from L. monocytogenes and lymphocytic choriomeningitis virus. Most of the studies agree that the nature and route of administration of these antigens affect the immune response in a particular location in the immune system, and that these two factors also influence the fate of T cells, which may proliferate and become effector cells, or else become anergic and die. Dendritic cells are crucial because they are the major population of antigenpresenting cells (APC) in the lymph nodes. The anatomical site of antigen presentation, but not the kind of APC, governs the type of immune response elicited [5].
Our laboratory developed a porous collagen matrix (PCM) from decellularized porcine dermis (PD) [6]. After considering current opinions on the methodology of immunotoxicity evaluation, in the present study, we used the implantation method to examine the systemic immune response to our biomaterial by counting CD4 þ and CD8 þ cells in the spleens of Sprague Dawley rats.

Materials and Methods
All experimental procedures were performed after obtaining approval from the committee on Animal Laboratory Procedures at the School of Medicine, National Cheng Kung University, Tainan, Taiwan. The study was conducted using 15 male Sprague Dawley rats (weight: 250-300 g) randomly assigned to three groups of five each. The rats were maintained in an air-conditioned environment and fed commercial rodent pellet feed and water ad libitum. Our test material [6], PCM, was subcutaneously implanted in the PCM group rats, and its immunotoxicity results were compared with unprocessed PD, used in the PD group, and a synthetic collagen matrix [DuraGen V R (DG); Integra LifeSciences Corporation, Plainsboro, NJ, USA], in the DG group.

Implantation procedure
Each rat was anesthetized using an intraperitoneal injection with combination (0.25 ml/100 g of body weight) of atropine (0.1 ml), ketamine hydrochloride (4 ml) (Ketala V R ; Pfizer, HsinChu, Taiwan), and 2% xylazine hydrochloride (1.34 ml) (Rompun V R ; Bayer Health Care, Monheim, Germany). After confirming that the rats did not respond to pain, their ventral trunk hair was clipped off. A subcutaneous pocket was created using a 1.25-cm incision. We chose the subcutaneous route based on a study [7] which reported that placing the antigen subcutaneously evoked a satisfactory response in CD4 þ and CD8 þ T cells. For each surgical procedure, an implant measuring 1.25 Â 1.25 cm was placed in the pocket created on the ventral aspect of the trunk. Serial implants of the same material were placed in non-adjacent pockets on days 0, 14, 19 and 28 of a 31-day experiment. The wounds were closed with nylon sutures. All rats were maintained for a sufficient period (1-3 days) in a warm environment during the recovery period. As such collagen-based materials are weakly immunogenic, we used serial implantation as an antigenic booster to increase the detectability of the immune response.

Spleen procurement and sample preparation
After 31 days, the spleens were harvested and the animals were killed with an overdose of sodium thiopental. Their spleens were weighed and single suspensions were prepared from them by gently squashing them with a syringe plunger and 10 ml of phosphate-buffered saline (PBS) solution in a Petri dish. The mixture obtained was filtered to obtain single-cell suspensions that were then centrifuged at 300Âg to collect cell pellets. After the pellets had been fixed, they were resuspended in PBS with 2% benzenesulfonic acid. We made two samples of resuspended cells from each rat's spleen and separately incubated each for 30 min with an excess of fluorescein isothiocyanate-conjugated mouse anti-rat CD4 monoclonal antibody and PE-anti-rat CD8a (both from BioLegend, San Diego, CA, USA). We identified lymphocyte subsets using a flow cytometer (FACScan; Becton Dickinson, Mountain View, CA, USA). The positive cells were expressed as a percentage of the 10,000 cells counted. Figure 1 shows representative data of the flow cytometry from all three groups for CD4 þ and CD8 þ cell counts in rat number 2.

Correlation of spleen weight and cytotoxicity
Increases in organ weights have been associated with immunotoxicity [8]. The weights of the spleens recorded are summarized in Table 2. The spleen weights of the rats were compared with the corresponding CD8 þ cell counts, which are the indicator of the cytotoxic cellular response ( Fig. 2A-C). Spleen weight and CD8 þ cell counts were not correlated in any group (Pearson Product-Moment Correlation test). Comparison of CD4 1 cell counts The mean CD4 þ cell counts were 24.5 6 3.6 for the PCM group, 25.5 6 7.1 for the DG group and 28.1 6 4.2 for the PD group (Fig. 3). Although the absolute values were the highest for the PD group, the differences in the mean values between groups were not significant (one-way analysis of variance (ANOVA)).

Comparison of CD8 1 cell counts
The mean and standard deviation of the CD8 þ cell counts were 19.8 6 4.0 for the PCM group, 21.6 6 3.8 for the DG group and 19.6 6 3.7 for the PD group (Fig. 3). Although the absolute values All values are expressed as a percentage of positive cells for the respective marker of 10,000 cells counted. SD, standard deviation.  of CD8 þ cell counts were marginally higher for the DG group, oneway ANOVA showed no significant difference between them.

Discussion
The safety of biomaterials intended for clinical use needs to be established by assessing their immunotoxicity response. International standards organizations such as American Society for Testing and Materials (ASTM) standard or International Organization for Standardization (ISO) have elaborate lists of tests that can be used. The biological response to subcutaneously injected collagenous implants has been histologically assessed by analyzing the tissue around the injected site [9]. The systemic immune response to subcutaneously implanted porcine collagen has been studied by quantifying antibodies in serum [10]. A tiered approach has been suggested as a logical method to choose from among these tests. Evaluating lymphocyte populations in the spleen is one of the tier II tests for evaluating cytotoxicity [11]. The International Conference of Harmonization ICH S8/step 4 document and the European Note for guidance on repeated dose toxicity (HCH 3BS2a, CPMP/SWP/1042/99) also suggest evaluating cytolytic lymphocytes (including CTL and NK cells) [12]. These lymphocytes contain azurophilic granules that accumulate at the site of contact with the target cells and suggest their involvement in cell-mediated killing [13,14]. These granules contain perforin (also called pore forming protein) and cytolysin which are responsible for cell lysis. Perforin is located with CD8 þ T cells and CD16 cells [15]. Azurophilic granules are absent in inactivated resting T cells.
Analyzing CD8 þ T cell populations may thus seem an optimal method for assessing the cytotoxic response to an implanted biomaterial. Choosing the appropriate tissue for evaluating CD4 þ and CD8 þ T cells, however, has been much debated. Another consideration in our study was the size of the implant to use, because this initial 'dose of antigen' may determine the number of CD8 þ T cells recruited. Contrary to the expectation that smaller doses of antigen can cause a lower response, it has been shown that, although smaller doses recruit fewer T cells, these cells become effector T cells with the ability to produce interferon, and become long-lived memory cells [16,17]. These findings governed our decision to use implants as small as 1.25 Â 1.25 cm.
Other considerations in designing our study were adopted from Organization for Economic Cooperation and Development (OECD) Test Guideline 407, which is primarily for testing pharmaceuticals [18]. Repeatedly inserting the same materials in noncontiguous locations was done so that it would act as an antigenic booster. Naïve CTLs become committed as soon as 2 h after they have been exposed to APCs [19]. Subsequent division and differentiation occur without needing further antigenic stimulation of daughter cells, which suggests the autonomous nature of CTL. Compared with this brief stimulatory period for CD8 þ CTL, about 24 h of continuous sustained signaling is required to prime CD4 þ CTL [20]. Despite the absence of antigens beyond day 2, T-cell division continues at a constant rate, and the antigen-independent later stage depends on the presence of interleukin (IL)-2. There are contrasting differences in both the duration of antigenic stimuli and the persistence of such stimuli required to optimally activate CTL; hence, we varied the duration of antigenic stimulation by retaining serial implants for 72 hours, 5 days and 14 days, which provided three advantages. First, it allowed for varying periods of antigenic persistence; second, it permitted us to obtain tissue for histopathology analysis at varying periods of time (data not shown); and, finally, repeated placements acted as immunogenic boosters that raised the immune response to detectable levels. CTL responses were neither pronounced nor significantly different between CD4 þ and CD8 þ T-cell counts in PCM or DG. Therefore, it may be inferred that the CD4 þ and CD8 þ T-cell responses for PCM are comparable to that of DG, a similar collagen matrix already in clinical use. However, conclusive evidence of the benefits of PCM or DG compared with PD will need larger trials and simultaneous comparisons of the cytotoxic responses in animals given sham operations and no biomaterial implants. Such a comparison might also shed light on T-cell response to a surgical wound in the spleen.
Increased organ weight has also been suggested as a method to gauge cytotoxicity [8]. Nevertheless, it is impractical to observe a trend in weight variation following repeated antigenic stimulation over a period of time in the study design. We compared the weight of the spleen at the end of the experiment with the corresponding CD8 þ cell counts, but found no correlation between spleen weights and CD8 þ cell counts, the indicator of cytotoxicity.
Individual CD4 þ cell counts were comparable between the three groups. CD4 þ cells are important for the CD8 cell response [16,17], which suggests that comparing CD8 cell counts was reliable. The mechanism of effect of CD4 cells was thought to be by providing IL-2, but recent studies [21,22] report that activation of dendritic cells serves as APCs for CD8 þ T cells, and that it is crucial for differentiating peripheral T cells into T H 1 and T H 2 cells [23].
The principal indicator of the degree of cytotoxicity in this study was the CD8 þ cell counts; there was no significant difference in these counts among PCM, DG and PD. However, their absolute values show a higher CD8 þ count for PCM than for PD. The explanation for this is that PCM used in test rats was heterogeneous because of minor technical differences in sterilizing and in preparing the biomaterials, which was done by different personnel. Our preliminary results were encouraging; however, because they showed that the in vivo immunotoxic response to our newly developed PCM biomaterial was similar to the response to DG, a similar collagenbased material currently in clinical use.

Conclusion
The present study may be the first attempt to study the systemic immune response by assaying activated lymphocytes in the spleen. It was a preliminary study and requires additional investigation and more convincing data. Standardizing the preparation of materials, including simultaneous comparisons with sham controls (rats Figure 3. Comparison of CD4 þ and CD8 þ cell counts (expressed as % of positive cells of 10,000 cells counted). Note: CD4 þ and CD8 þ cell counts were similar in the PCM, DG and PD groups; differences were not significant. without implanted biomaterials), and assessing circulating CD4 þ and CD8 þ T cells in peripheral blood are required to obtain confirmatory evidence of the level of toxicity.