Unsupervised deep learning model for correcting Nyquist ghosts of single-shot spatiotemporal encoding.

PURPOSE: To design an unsupervised deep learning (DL) model for correcting Nyquist ghosts of single-shot spatiotemporal encoding (SPEN) and evaluate the model for real MRI applications. METHODS: The proposed method consists of three main components: (1) an unsupervised network that combines Residual Encoder and Restricted Subspace Mapping (RERSM-net) and is trained to generate a phase-difference map based on the even and odd SPEN images; (2) a spin physical forward model to obtain the corrected image with the learned phase difference map; and (3) cycle-consistency loss that is explored for training the RERSM-net. RESULTS: The proposed RERSM-net could effectively generate smooth phase difference maps and correct Nyquist ghosts of single-shot SPEN. Both simulation and real in vivo MRI experiments demonstrated that our method outperforms the state-of-the-art SPEN Nyquist ghost correction method. Furthermore, the ablation experiments of generating phase-difference maps show the advantages of the proposed unsupervised model. CONCLUSION: The proposed method can effectively correct Nyquist ghosts for the single-shot SPEN sequence.

Relaxation-Diffusion T2-ADC Correlations in Breast Cancer Patients: A Spatiotemporally Encoded 3T MRI Assessment.

Quantitative correlations between T2 and ADC values were explored on cancerous breast lesions using spatiotemporally encoded (SPEN) MRI. To this end, T2 maps of patients were measured at more than one b-value, and ADC maps at several echo time values were recorded. SPEN delivered quality, artifact-free, TE-weighted DW images, from which T2-ADC correlations could be obtained despite the signal losses brought about by diffusion and relaxation. Data confirmed known aspects of breast cancer lesions, including their reduced ADC values vs. healthy tissue. Data also revealed an anticorrelation between the T2 and ADC values, when comparing regions with healthy and diseased tissues. This is contrary to expectations based on simple water restriction considerations. It is also contrary to what has been observed in a majority of porous materials and tissues. Differences between the healthy tissue of the lesion-affected breast and healthy tissue in the contralateral breast were also noticed. The potential significance of these trends is discussed, as is the potential of combining T2- and ADC-weightings to achieve an enhanced endogenous MRI contrast about the location of breast cancer lesions.

Unsupervised cycle-consistent network using restricted subspace field map for removing susceptibility artifacts in EPI.

PURPOSE: To design an unsupervised deep neural model for correcting susceptibility artifacts in single-shot Echo Planar Imaging (EPI) and evaluate the model for preclinical and clinical applications. METHODS: This work proposes an unsupervised cycle-consistent model based on the restricted subspace field map to take advantage of both the deep learning (DL) and the reverse polarity-gradient (RPG) method for single-shot EPI. The proposed model consists of three main components: (1) DLRPG neural network (DLRPG-net) to obtain field maps based on a pair of images acquired with reversed phase encoding; (2) spin physical model-based modules to obtain the corrected undistorted images based on the learned field map; and (3) cycle-consistency loss between the input images and back-calculated images from each cycle is explored for network training. In addition, the field maps generated by DLRPG-net belong to a restricted subspace, which is a span of predefined cubic splines to ensure the smoothness of the field maps and avoid blurring in the corrected images. This new method is trained and validated on both preclinical and clinical datasets for diffusion MRI. RESULTS: The proposed network could effectively generate smooth field maps and correct susceptibility artifacts in single-shot EPI. Simulated and in vivo preclinical/clinical experiments demonstrated that our method outperforms the state-of-the-art susceptibility artifact correction methods. Furthermore, the ablation experiments of the cycle-consistent network and the restricted subspace in generating field maps did show the advantages of DLRPG-net. CONCLUSION: The proposed method (DLRPG-net) can effectively correct susceptibility artifacts for preclinical and clinical single-shot EPI sequences.

Prostate lesions characterization using diffusion-weighted spatiotemporal encoded MRI: Feasibility and initial assessment.

PURPOSE: To assess the feasibility and reliability of a DWI protocol based on spatiotemporally encoding (SPEN), to target prostate lesions along guidelines normally used in EPI-based DWI clinical practice. METHODS: Prostate Imaging-Reporting and Data System recommendations underlying clinical prostate scans were used to develop a SPEN-based DWI protocol, which included a novel, local, low-rank regularization algorithm. These DWI acquisitions were run at 3 T under similar nominal spatial resolutions and diffusion-weighting b-values as used in EPI-based clinical studies. Prostates of 11 patients suspected of clinically significant prostate cancer lesions were therefore scanned using the two methods, with the same number of slices, same slice thickness, and same interslice gaps. RESULTS: Of the 11 patients scanned, SPEN and EPI provided comparable information in 7 of the cases, whereas EPI was deemed superior in a case for which SPEN images had to be acquired with a shorter effective TR owing to scan-time constraints. SPEN provided reduced susceptibility to field-derived distortions in 3 of the cases. CONCLUSIONS: SPEN's ability to provide prostate lesion contrast was most clearly evidenced for DW images acquired with b ≥ 900 s/mm2 . SPEN also succeeded in decreasing occasional image distortions in regions close to the rectum, affected by field inhomogeneities. EPI advantages arose when using short effective TRs, a regime in which SPEN-based DWI was handicapped by its use of nonselective spin inversions, leading to the onset of an additional T1 weighting.

Mutually communicated model based on multi-parametric MRI for automated segmentation and classification of prostate cancer.

BACKGROUND: Multiparametric magnetic resonance imaging (mp-MRI) is introduced and established as a noninvasive alternative for prostate cancer (PCa) detection and characterization. PURPOSE: To develop and evaluate a mutually communicated deep learning segmentation and classification network (MC-DSCN) based on mp-MRI for prostate segmentation and PCa diagnosis. METHODS: The proposed MC-DSCN can transfer mutual information between segmentation and classification components and facilitate each other in a bootstrapping way. For classification task, the MC-DSCN can transfer the masks produced by the coarse segmentation component to the classification component to exclude irrelevant regions and facilitate classification. For segmentation task, this model can transfer the high-quality localization information learned by the classification component to the fine segmentation component to mitigate the impact of inaccurate localization on segmentation results. Consecutive MRI exams of patients were retrospectively collected from two medical centers (referred to as center A and B). Two experienced radiologists segmented the prostate regions, and the ground truth of the classification refers to the prostate biopsy results. MC-DSCN was designed, trained, and validated using different combinations of distinct MRI sequences as input (e.g., T2-weighted and apparent diffusion coefficient) and the effect of different architectures on the network's performance was tested and discussed. Data from center A were used for training, validation, and internal testing, while another center's data were used for external testing. The statistical analysis is performed to evaluate the performance of the MC-DSCN. The DeLong test and paired t-test were used to assess the performance of classification and segmentation, respectively. RESULTS: In total, 134 patients were included. The proposed MC-DSCN outperforms the networks that were designed solely for segmentation or classification. Regarding the segmentation task, the classification localization information helped to improve the IOU in center A: from 84.5% to 87.8% (p < 0.01) and in center B: from 83.8% to 87.1% (p < 0.01), while the area under curve (AUC) of PCa classification was improved in center A: from 0.946 to 0.991 (p < 0.02) and in center B: from 0.926 to 0.955 (p < 0.01) as a result of the additional information provided by the prostate segmentation. CONCLUSION: The proposed architecture could effectively transfer mutual information between segmentation and classification components and facilitate each other in a bootstrapping way, thus outperforming the networks designed to perform only one task.

Arterial spin labeling using spatio-temporal encoding readout for robust perfusion imaging in inhomogenous magnetic fields.

PURPOSE: To evaluate the feasibility of spatio-temporal encoding (SPEN) readout for pseudo-continuous ASL (pCASL) in brain, and its robustness to susceptibility artifacts as introduced by aneurysm clips. METHODS: A 2D self-refocused T2 *-compensated hybrid SPEN scheme, with super-resolution reconstruction was implemented on a 1.5T Philips system. Q (=BWchirp *Tchirp ) was varied and, the aneurysm clip-induced artifact was evaluated in phantom (label-images) as well as in vivo (perfusion-weighted signal (PWS)-maps and temporal SNR (tSNR)). In vivo results were compared to gradient-echo EPI (GE-EPI) and spin-echo EPI (SE-EPI). The dependence of tSNR on TR was evaluated separately for SPEN and SE-EPI. SPEN with Q Ëœ 75 encodes with the same off-resonance robustness as EPI. RESULTS: The clip-induced artifact with SPEN decreased with increase in Q, and was smaller compared to SE-EPI and GE-EPI in vivo. tSNR decreased with Q and the tSNR of GE-EPI and SE-EPI corresponded to SPEN with a Q-value of approximately ˜85 and ˜108, respectively. In addition, SPEN perfusion images showed a higher tSNR (p < 0.05) for TR = 4000 ms compared to TR = 2100 ms, while SE-EPI did not. tSNR remained relatively stable when the time between SPEN-excitation and start of the next labeling-module was more than ˜1000 ms. CONCLUSION: Feasibility of combining SPEN with pCASL imaging was demonstrated, enabling cerebral perfusion measurements with a higher robustness to field inhomogeneity (Q > 75) compared to SE-EPI and GE-EPI. However, the SPEN chirp-pulse saturates incoming blood, thereby reducing pCASL labeling efficiency of the next acquisition for short TRs. Future developments are needed to enable 3D scanning.

Spatiotemporal encoding MRI using subspace-constrained sampling and locally-low-rank regularization: Applications to diffusion weighted and diffusion kurtosis imaging of human brain and prostate.

The benefits of performing locally low-rank (LLR) reconstructions on subsampled diffusion weighted and diffusion kurtosis imaging data employing spatiotemporal encoding (SPEN) methods, is investigated. SPEN allows for self-referenced correction of motion-induced phase errors in case of interleaved diffusion-oriented acquisitions, and allows one to overcome distortions otherwise observed along EPI's phase-encoded dimension. In combination with LLR-based reconstructions of the pooled imaging data and with a joint subsampling of b-weighted and interleaved images, additional improvements in terms of sensitivity as well as shortened acquisition times are demonstrated, without noticeable penalties. Details on how the LLR-regularized, subspace-constrained image reconstructions were adapted to SPEN are given; the improvements introduced by adopting these reconstruction frameworks for the accelerated acquisition of diffusivity and of kurtosis imaging data in both relatively homogeneous regions like the human brain and in more challenging regions like the human prostate, are presented and discussed within the context of similar efforts in the field.

Solution Structure of Tubuliform Spidroin N-Terminal Domain and Implications for pH Dependent Dimerization.

The spidroin N-terminal domain (NT) is responsible for high solubility and pH-dependent assembly of spider silk proteins during storage and fiber formation, respectively. It forms a monomeric five-helix bundle at neutral pH and dimerizes at lowered pH, thereby firmly interconnecting the spidroins. Mechanistic studies with the NTs from major ampullate, minor ampullate, and flagelliform spidroins (MaSp, MiSp, and FlSp) have shown that the pH dependency is conserved between different silk types, although the residues that mediate this process can differ. Here we study the tubuliform spidroin (TuSp) NT from Argiope argentata, which lacks several well conserved residues involved in the dimerization of other NTs. We solve its structure at low pH revealing an antiparallel dimer of two five-α-helix bundles, which contrasts with a previously determined Nephila antipodiana TuSp NT monomer structure. Further, we study a set of mutants and find that the residues participating in the protonation events during dimerization are different from MaSp and MiSp NT. Charge reversal of one of these residues (R117 in TuSp) results in significantly altered electrostatic interactions between monomer subunits. Altogether, the structure and mutant studies suggest that TuSp NT monomers assemble by elimination of intramolecular repulsive charge interactions, which could lead to slight tilting of α-helices.

Simultaneous multi-banding and multi-echo phase encoding for the accelerated acquisition of high-resolution volumetric diffusivity maps by spatiotemporally encoded MRI.

PURPOSE: Spatiotemporal Encoding (SPEN) is an ultrafast imaging technique where the low-bandwidth axis is rasterized in a joint spatial/k-domain. SPEN benefits from increased robustness to field inhomogeneities, folding-free reconstruction of subsampled data, and an ability to combine multiple interleaved or signal averaged scans -yet its relatively high SAR complicates volumetric uses. Here we show how this can be alleviated by merging simultaneous multi-band excitation, with intra-slab multi-echo (ME) phase encoding, for the acquisition of high definition volumetric DWI/DTI data. METHODS: A protocol involving phase-cycling of simultaneous multi-banded z-slab excitations in independently ky-interleaved scans, together with ME trains that kz-encoded positions within these slabs, was implemented. A reconstruction incorporating a CAIPIRINHA-like encoding of the multiple bands and exploiting SPEN's ability to deliver self-referenced, per-shot phase maps, then led to high-definition diffusivity acquisitions, with reduced SAR and acquisition times vis-à-vis non-optimized 3D counterparts. RESULTS: The new protocol was used to collect full brain 3 T DTI experiments at a variety of nominal voxel sizes, ranging from 1.95 to 2.54 mm3. In general, the new protocol yielded superior sensitivity and fewer distortions than what could be observed in comparably timed phase-encoded 3D SPEN, multi-slice 2D SPEN, or optimized EPI counterparts. CONCLUSIONS: A robust procedure for acquiring volumetric DWI/DTI data was developed and demonstrated.

Diffusivity in breast malignancies analyzed for b > 1000 s/mm2 at 1 mm in-plane resolutions: Insight from Gaussian and non-Gaussian behaviors.

Diffusion-weighted imaging (DWI) can improve breast cancer characterizations, but often suffers from low image quality -particularly at informative b > 1000 s/mm2 values. The aim of this study was to evaluate multishot approaches characterizing Gaussian and non-Gaussian diffusivities in breast cancer. This was a prospective study, in which 15 subjects, including 13 patients with biopsy-confirmed breast cancers, were enrolled. DWI was acquired at 3 T using echo planar imaging (EPI) with and without zoomed excitations, readout-segmented EPI (RESOLVE), and spatiotemporal encoding (SPEN); dynamic contrast-enhanced (DCE) data were collected using three-dimensional gradient-echo T1 weighting; anatomies were evaluated with T2 -weighted two-dimensional turbo spin-echo. Congruence between malignancies delineated by DCE was assessed against high-resolution DWI scans with b-values in the 0-1800 s/mm2 range, as well as against apparent diffusion coefficient (ADC) and kurtosis maps. Data were evaluated by independent magnetic resonance scientists with 3-20 years of experience, and radiologists with 6 and 20 years of experience in breast MRI. Malignancies were assessed from ADC and kurtosis maps, using paired t tests after confirming that these values had a Gaussian distribution. Agreements between DWI and DCE datasets were also evaluated using Sorensen-Dice similarity coefficients. Cancerous and normal tissues were clearly separable by ADCs: by SPEN their average values were (1.03 ± 0.17) × 10-3 and (1.69 ± 0.19) × 10-3  mm2 /s (p < 0.0001); by RESOLVE these values were (1.16 ± 0.16) × 10-3 and (1.52 ± 0.14) × 10-3 (p = 0.00026). Kurtosis also distinguished lesions (K = 0.64 ± 0.15) from normal tissues (K = 0.45 ± 0.05), but only when measured by SPEN (p = 0.0008). The best statistical agreement with DCE-highlighted regions arose for SPEN-based DWIs recorded with b = 1800 s/mm2 (Sorensen-Dice coefficient = 0.67); DWI data recorded with b = 850 and 1200 s/mm2 , led to lower coefficients. Both ADC and kurtosis maps highlighted the breast malignancies, with ADCs providing a more significant separation. The most promising alternative for contrast-free delineations of the cancerous lesions arose from b = 1800 s/mm2 DWI. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 3.

Solution NMR structure of Borrelia burgdorferi outer surface lipoprotein BBP28, a member of the mlp protein family.

Lyme disease is the most widespread vector-transmitted disease in North America and Europe, caused by infection with Borrelia burgdorferi sensu lato complex spirochetes. We report the solution NMR structure of the B. burgdorferi outer surface lipoprotein BBP28, a member of the multicopy lipoprotein (mlp) family. The structure comprises a tether peptide, five α-helices and an extended C-terminal loop. The fold is similar to that of Borrelia turicatae outer surface protein BTA121, which is known to bind lipids. These results contribute to the understanding of Lyme disease pathogenesis by revealing the molecular structure of a protein from the widely found mlp family.

A regularized reconstruction pipeline for high-definition diffusion MRI in challenging regions incorporating a per-shot image correction.

PURPOSE: Diffusion MRI is of interest for clinical research and diagnosis. Whereas high- resolution DWI/DTI is hard to achieve by single-shot methods, interleaved acquisitions can deliver these if motion and/or folding artefacts are overcome. Thanks to its ability to provide zoomed, folding-free images, spatially encoded MRI can fulfill these requirements. This is here coupled with a regularized reconstruction and parallel receive methods, to deliver a robust scheme for human DWI/DTI at mm and sub-mm resolutions. METHODS: Each shot along the spatially encoded dimension was reconstructed separately to retrieve per-shot phase maps. These shots, together with coil sensitivities, were combined with spatially encoded quadratic phase-encoding matrices associated to each shot, into single global operators. Their originating images were then iteratively computed aided by l1 and l2 regularization methods. When needed, motion-corrupted shots were discarded and replaced by redundant information arising from parallel imaging. RESULTS: Full-brain DTI experiments at 1 mm and restricted brain DTIs with 0.75 mm nominal in-plane resolutions were acquired and reconstructed successfully by the new scheme. These 3 Tesla spetiotemporally encoded results compared favorably with EPI counterparts based on segmented and selective excitation schemes provided with the scanner. CONCLUSION: A new procedure for achieving high-definition diffusion-based MRI was developed and demonstrated.

Natural Abundance, Single-Scan 13C-13C-Based Structural Elucidations by Dissolution DNP NMR.

While 13C-based Incredible Natural Abundance DoublE QUAntum Transfer Experiment (INADEQUATE) experiments offer an attractive alternative for establishing molecular structures, they suffer from low sensitivities arising from the scarcity of spin pairs present at natural abundance. Herein we demonstrate that dissolution dynamic nuclear polarization (dDNP) provides sufficient sensitivity to acquire 1D 13C INADEQUATE spectra in a single scan and at natural abundance. Moreover, if steps are adopted to endow sub-Hertz precision to these measurements, they allow one to measure carbon-carbon J couplings over both one and multiple bonds for each chemical site. As these JCC-couplings are usually sufficiently distinct to enable univocal pairing of the nuclei involved, essentially the same information as in 2D INADEQUATE can be obtained. The feasibility of the method is demonstrated for a range of compounds, including natural products such as α-pinene, menthol and limonene. Features and extensions of this approach are briefly discussed.

Degree of Biomimicry of Artificial Spider Silk Spinning Assessed by NMR Spectroscopy.

Biomimetic spinning of artificial spider silk requires that the terminal domains of designed minispidroins undergo specific structural changes in concert with the ß-sheet conversion of the repetitive region. Herein, we combine solution and solid-state NMR methods to probe domain-specific structural changes in the NT2RepCT minispidroin, which allows us to assess the degree of biomimicry of artificial silk spinning. In addition, we show that the structural effects of post-spinning procedures can be examined. By studying the impact of NT2RepCT fiber drying, we observed a reversible beta-to-alpha conversion. We think that this approach will be useful for guiding the optimization of artificial spider silk fibers.

Efficient protein production inspired by how spiders make silk.

Membrane proteins are targets of most available pharmaceuticals, but they are difficult to produce recombinantly, like many other aggregation-prone proteins. Spiders can produce silk proteins at huge concentrations by sequestering their aggregation-prone regions in micellar structures, where the very soluble N-terminal domain (NT) forms the shell. We hypothesize that fusion to NT could similarly solubilize non-spidroin proteins, and design a charge-reversed mutant (NT*) that is pH insensitive, stabilized and hypersoluble compared to wild-type NT. NT*-transmembrane protein fusions yield up to eight times more of soluble protein in Escherichia coli than fusions with several conventional tags. NT* enables transmembrane peptide purification to homogeneity without chromatography and manufacture of low-cost synthetic lung surfactant that works in an animal model of respiratory disease. NT* also allows efficient expression and purification of non-transmembrane proteins, which are otherwise refractory to recombinant production, and offers a new tool for reluctant proteins in general.

Fragment-Based Discovery of 2-Aminoquinazolin-4(3H)-ones As Novel Class Nonpeptidomimetic Inhibitors of the Plasmepsins I, II, and IV.

2-Aminoquinazolin-4(3H)-ones were identified as a novel class of malaria digestive vacuole plasmepsin inhibitors by using NMR-based fragment screening against Plm II. Initial fragment hit optimization led to a submicromolar inhibitor, which was cocrystallized with Plm II to produce an X-ray structure of the complex. The structure showed that 2-aminoquinazolin-4(3H)-ones bind to the open flap conformation of the enzyme and provided clues to target the flap pocket. Further improvement in potency was achieved via introduction of hydrophobic substituents occupying the flap pocket. Most of the 2-aminoquinazolin-4(3H)-one based inhibitors show a similar activity against digestive Plms I, II, and IV and >10-fold selectivity versus CatD, although varying the flap pocket substituent led to one Plm IV selective inhibitor. In cell-based assays, the compounds show growth inhibition of Plasmodium falciparum 3D7 with IC50 ∼ 1 µM. Together, these results suggest 2-aminoquinazolin-4(3H)-ones as perspective leads for future development of an antimalarial agent.

Diversified Structural Basis of a Conserved Molecular Mechanism for pH-Dependent Dimerization in Spider Silk N-Terminal Domains.

Conversion of spider silk proteins from soluble dope to insoluble fibers involves pH-dependent dimerization of the N-terminal domain (NT). This conversion is tightly regulated to prevent premature precipitation and enable rapid silk formation at the end of the duct. Three glutamic acid residues that mediate this process in the NT from Euprosthenops australis major ampullate spidroin 1 are well conserved among spidroins. However, NTs of minor ampullate spidroins from several species, including Araneus ventricosus ((Av)MiSp NT), lack one of the glutamic acids. Here we investigate the pH-dependent structural changes of (Av)MiSp NT, revealing that it uses the same mechanism but involves a non-conserved glutamic acid residue instead. Homology modeling of the structures of other MiSp NTs suggests that these harbor different compensatory residues. This indicates that, despite sequence variations, the molecular mechanism underlying pH-dependent dimerization of NT is conserved among different silk types.

Carbonic anhydrase generates CO2 and H+ that drive spider silk formation via opposite effects on the terminal domains.

Spider silk fibers are produced from soluble proteins (spidroins) under ambient conditions in a complex but poorly understood process. Spidroins are highly repetitive in sequence but capped by nonrepetitive N- and C-terminal domains (NT and CT) that are suggested to regulate fiber conversion in similar manners. By using ion selective microelectrodes we found that the pH gradient in the silk gland is much broader than previously known. Surprisingly, the terminal domains respond in opposite ways when pH is decreased from 7 to 5: Urea denaturation and temperature stability assays show that NT dimers get significantly stabilized and then lock the spidroins into multimers, whereas CT on the other hand is destabilized and unfolds into ThT-positive ß-sheet amyloid fibrils, which can trigger fiber formation. There is a high carbon dioxide pressure (pCO2) in distal parts of the gland, and a CO2 analogue interacts with buried regions in CT as determined by nuclear magnetic resonance (NMR) spectroscopy. Activity staining of histological sections and inhibition experiments reveal that the pH gradient is created by carbonic anhydrase. Carbonic anhydrase activity emerges in the same region of the gland as the opposite effects on NT and CT stability occur. These synchronous events suggest a novel CO2 and proton-dependent lock and trigger mechanism of spider silk formation.

Plasmepsin inhibitory activity and structure-guided optimization of a potent hydroxyethylamine-based antimalarial hit.

Antimalarial hit 1 SR (TCMDC-134674) identified in a GlaxoSmithKline cell based screening campaign was evaluated for inhibitory activity against the digestive vacuole plasmepsins (Plm I, II, and IV). It was found to be a potent Plm IV inhibitor with no selectivity over Cathepsin D. A cocrystal structure of 1 SR bound to Plm II was solved, providing structural insight for the design of more potent and selective analogues. Structure-guided optimization led to the identification of structurally simplified analogues 17 and 18 as low nanomolar inhibitors of both, plasmepsin Plm IV activity and P. falciparum growth in erythrocytes.

Structural characterization of CspZ, a complement regulator factor H and FHL-1 binding protein from Borrelia burgdorferi.

Borrelia burgdorferi is the causative agent of Lyme disease and is found in two different types of hosts in nature - Ixodes ticks and various mammalian organisms. To initiate disease and survive in mammalian host organisms, B. burgdorferi must be able to transfer to a new host, proliferate, attach to different tissue and resist the immune response. To resist the host's immune response, B. burgdorferi produces at least five different outer surface proteins that can bind complement regulator factor H (CFH) and/or factor H-like protein 1 (CFHL-1). The crystal structures of two uniquely folded complement binding proteins, which belong to two distinct gene families and are not found in other bacteria, have been previously described. The crystal structure of the CFH and CFHL-1 binding protein CspZ (also known as BbCRASP-2 or BBH06) from B. burgdorferi, which belongs to a third gene family, is reported in this study. The structure reveals that the overall fold is different from the known structures of the other complement binding proteins in B. burgdorferi or other bacteria; this structure does not resemble the fold of any known protein deposited in the Protein Data Bank. The N-terminal part of the CspZ protein forms a four-helix bundle and has features similar to the FAT domain (focal adhesion targeting domain) and a related domain found in the vinculin/α-catenin family. By combining our findings from the crystal structure of CspZ with previous mutagenesis studies, we have identified a likely binding surface on CspZ for CFH and CFHL-1.