Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems

Application of Immunohistochemistry in Clinical Practices as a Standardized Assay for Breast Cancer

Immunohistochemistry (IHC) has become an indispensable tool in the clinical practices for breast cancer; however, to achieve its standardization, numerous issues need to be overcome. In this review, we describe the development of IHC as an important clinical tool, and the challenges in standardizing IHC results for patients. We also present ideas for resolving the remaining issues and unmet needs, along with future directions.

Comparison of the Toponomes of Alveolar Macrophages From Wild Type and Surfactant Protein A Knockout Mice and Their Response to Infection

Background

Surfactant protein-A (SP-A) plays a critical role in lung innate immunity by regulating alveolar macrophages (AM), expression of inflammatory mediators, and other host defense proteins. The toponome imaging system (TIS), a serial immunostainer, was used to study the AM toponome because it characterizes the localization of multiple markers and identifies marker combinations in each pixel as combinatorial molecular phenotypes (CMPs). We used TIS to study the AM toponome from wild type (WT) and SP-A knockout (KO) mice and changes following Klebsiella pneumoniae exposure.

Methods

WT or KO mice received intratracheal K. pneumoniae or vehicle and AM were obtained by bronchoalveolar lavage after one hour. AM were attached to slides and underwent TIS analysis. Images were analyzed to characterize all pixels. AM CMPs from WT vehicle (n=3) and infected (n=3) mice were compared to each other and to AM from KO (n=3 vehicle; n=3 infected). Histograms provided us with a tool to summarize the representation of each marker in a set of CMPs.

Results

Using the histograms and other tools we identified markers of interest and observed that: 1) Both comparisons had conserved (present in all group members) CMPs, only in vehicle AM and only in infected AM, or common to both vehicle and infected AM, (i.e., unaffected by the condition). 2) the CMP number decreased with infection in WT and KO versus vehicle controls. 3) More infection-specific CMPs in WT vs KO AM. 4) When AM from WT and KO vehicle or infected were compared, there were more unique CMPs exclusive to the KO AM. 5) All comparisons showed CMPs shared by both groups.

Conclusions

The decrease of CMPs exclusive to infected AM in KO mice may underlie the observed susceptibility of KO mice to infection. However, both KO groups had more exclusive CMPs than the corresponding WT groups, perhaps indicating a vigorous effort by KO to overcome deficits in certain proteins and CMPs that are dysregulated by the absence of SP-A. Moreover, the presence of shared CMPs in the compared groups indicates that regulation of these CMPs is not dependent on either infection or the presence or absence of SP-A.

The alveolar macrophage toponome of female SP-A knockout mice differs from that of males before and after SP-A1 rescue

Using the Toponome Imaging System (TIS), a serial immunostainer, we studied the patterns of expression of multiple markers in alveolar macrophages (AM) from female mice lacking surfactant protein A (SP-A knockouts; KO) after "rescue" with exogenous SP-A1. We also used a 7-marker subset to compare with AM from males. AM were harvested 18 h after intrapharyngeal SP-A1 or vehicle, attached to slides, and subjected to serial immunostaining for 12 markers. Expression of the markers in each pixel of the image was analyzed both in the whole image and in individual selected cells. The marker combination in each pixel is referred to as a combinatorial molecular phenotype (CMP). A subset of antibodies was used to compare AM from male mice to the females. We found: (a) extensive AM heterogeneity in females by CMP analysis and by clustering analysis of CMPs in single cells; (b) AM from female KO mice respond to exogenous SP-A1 by increasing CMP phenotypic diversity and perhaps enhancing their potential innate immune capabilities; and (c) comparison of male and female AM responses to SP-A1 revealed that males respond more vigorously than females and clustering analysis was more effective in distinguishing males from females rather than treated from control.

Human Surfactant Protein SP-A1 and SP-A2 Variants Differentially Affect the Alveolar Microenvironment, Surfactant Structure, Regulation and Function of the Alveolar Macrophage, and Animal and Human Survival Under Various Conditions

The human innate host defense molecules, SP-A1 and SP-A2 variants, differentially affect survival after infection in mice and in lung transplant patients. SP-A interacts with the sentinel innate immune cell in the alveolus, the alveolar macrophage (AM), and modulates its function and regulation. SP-A also plays a role in pulmonary surfactant-related aspects, including surfactant structure and reorganization. For most (if not all) pulmonary diseases there is a dysregulation of host defense and inflammatory processes and/or surfactant dysfunction or deficiency. Because SP-A plays a role in both of these general processes where one or both may become aberrant in pulmonary disease, SP-A stands to be an important molecule in health and disease. In humans (unlike in rodents) SP-A is encoded by two genes (SFTPA1 and SFTPA2) and each has been identified with extensive genetic and epigenetic complexity. In this review, we focus on functional, structural, and regulatory differences between the two SP-A gene-specific products, SP-A1 and SP-A2, and among their corresponding variants. We discuss the differential impact of these variants on the surfactant structure, the alveolar microenvironment, the regulation of epithelial type II miRNome, the regulation and function of the AM, the overall survival of the organism after infection, and others. Although there have been a number of reviews on SP-A, this is the first review that provides such a comprehensive account of the differences between human SP-A1 and SP-A2.

Using toponomics to characterize phenotypic diversity in alveolar macrophages from male mice treated with exogenous SP-A1

Background

We used the Toponome Imaging System (TIS) to identify “patterns of marker expression”, referred to here as combinatorial molecular phenotypes (CMPs) in alveolar macrophages (AM) in response to the innate immune molecule, SP-A1.

Methods

We compared 114 AM from male SP-A deficient mice. One group (n = 3) was treated with exogenous human surfactant protein A1 (hSP-A1) and the other with vehicle (n = 3). AM obtained by bronchoalveolar lavage were plated onto slides and analyzed using TIS to study the AM toponome, the spatial network of proteins within intact cells. With TIS, each slide is sequentially immunostained with multiple FITC-conjugated antibodies. Images are analyzed pixel-by-pixel identifying all of the proteins within each pixel, which are then designated as CMPs. CMPs represent organized protein clusters postulated to contribute to specific functions.

Results

1) We compared identical CMPs in KO and SP-A1 cells and found them to differ significantly (p = 0.0007). Similarities between pairs of markers in the two populations also differed significantly (p < 0.0001). 2) Focusing on the 20 most abundant CMPs for each cell, we developed a method to generate CMP “signatures” that characterized various groups of cells. Phenotypes were defined as cells exhibiting similar signatures of CMPs. i) AM were extremely diverse and each group contained cells with multiple phenotypes. ii) Among the 114 AM analyzed, no two cells were identical. iii) However, CMP signatures could distinguish among cell subpopulations within and between groups. iv) Some cell populations were enriched with SP-A1 treatment, some were more common without SP-A1, and some seemed not to be influenced by the presence of SP-A1. v) We also found that AM were more diverse in mice treated with SP-A1 compared to those treated with vehicle.

Conclusions

AM diversity is far more extensive than originally thought. The increased diversity of SP-A1-treated mice points to the possibility that SP-A1 enhances or activates several pathways in the AM to better prepare it for its innate immune functions and other functions shown previously to be affected by SP-A treatment. Future studies may identify key protein(s) responsible for CMP integrity and consequently for a given function, and target it for therapeutic purposes.

Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures

Background

Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view.

Results

The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence.

Conclusions

MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information).

Nature and Consequences of Biological Reductionism for the Immunological Study of Infectious Diseases

Evolution has conserved "economic" systems that perform many functions, faster or better, with less. For example, three to five leukocyte types protect from thousands of pathogens. To achieve so much with so little, biological systems combine their limited elements, creating complex structures. Yet, the prevalent research paradigm is reductionist. Focusing on infectious diseases, reductionist and non-reductionist views are here described. The literature indicates that reductionism is associated with information loss and errors, while non-reductionist operations can extract more information from the same data. When designed to capture one-to-many/many-to-one interactions-including the use of arrows that connect pairs of consecutive observations-non-reductionist (spatial-temporal) constructs eliminate data variability from all dimensions, except along one line, while arrows describe the directionality of temporal changes that occur along the line. To validate the patterns detected by non-reductionist operations, reductionist procedures are needed. Integrated (non-reductionist and reductionist) methods can (i) distinguish data subsets that differ immunologically and statistically; (ii) differentiate false-negative from -positive errors; (iii) discriminate disease stages; (iv) capture in vivo, multilevel interactions that consider the patient, the microbe, and antibiotic-mediated responses; and (v) assess dynamics. Integrated methods provide repeatable and biologically interpretable information.

Structure-Based Reverse Vaccinology Failed in the Case of HIV Because it Disregarded Accepted Immunological Theory

Two types of reverse vaccinology (RV) should be distinguished: genome-based RV for bacterial vaccines and structure-based RV for viral vaccines. Structure-based RV consists in trying to generate a vaccine by first determining the crystallographic structure of a complex between a viral epitope and a neutralizing monoclonal antibody (nMab) and then reconstructing the epitope by reverse molecular engineering outside the context of the native viral protein. It is based on the unwarranted assumption that the epitope designed to fit the nMab will have acquired the immunogenic capacity to elicit a polyclonal antibody response with the same protective capacity as the nMab. After more than a decade of intensive research using this type of RV, this approach has failed to deliver an effective, preventive HIV-1 vaccine. The structure and dynamics of different types of HIV-1 epitopes and of paratopes are described. The rational design of an anti-HIV-1 vaccine is shown to be a misnomer since investigators who claim that they design a vaccine are actually only improving the antigenic binding capacity of one epitope with respect to only one paratope and not the immunogenic capacity of an epitope to elicit neutralizing antibodies. Because of the degeneracy of the immune system and the polyspecificity of antibodies, each epitope studied by the structure-based RV procedure is only one of the many epitopes that the particular nMab is able to recognize and there is no reason to assume that this nMab must have been elicited by this one epitope of known structure. Recent evidence is presented that the trimeric Env spikes of the virus possess such an enormous plasticity and intrinsic structural flexibility that it is it extremely difficult to determine which Env regions are the best candidate vaccine immunogens most likely to elicit protective antibodies.

Highly Multiplexed Imaging Uncovers Changes in Compositional Noise within Assembling Focal Adhesions

Integrin adhesome proteins bind each other in alternative manners, forming within the cell diverse cell-matrix adhesion sites with distinct properties. An intriguing question is how such modular assembly of adhesion sites is achieved correctly solely by self-organization of their components. Here we address this question using high-throughput multiplexed imaging of eight proteins and two phosphorylation sites in a large number of single focal adhesions. We found that during the assembly of focal adhesions the variances of protein densities decrease while the correlations between them increase, suggesting reduction in the noise levels within these structures. These changes correlate independently with the area and internal density of focal adhesions, but not with their age or shape. Artificial neural network analysis indicates that a joint consideration of multiple components improves the predictability of paxillin and zyxin levels in internally dense focal adhesions. This suggests that paxillin and zyxin densities in focal adhesions are fine-tuned by integrating the levels of multiple other components, thus averaging-out stochastic fluctuations. Based on these results we propose that increase in internal protein densities facilitates noise suppression in focal adhesions, while noise suppression enables their stable growth and further density increase—hence forming a feedback loop giving rise to a quality-controlled assembly.

A Generalized Spatial Measure for Resilience of Microbial Systems

The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. However, this spatial metric of resilience is limited to use for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (for example, either sharp or smooth gradients). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century’s work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Large molecular systems landscape uncovers T cell trapping in human skin cancer

Immune surveillance of tumour cells is an important function of CD8 T lymphocytes, which has failed in cancer for reasons still unknown in many respect but mainly related to cellular processes in the tumour microenvironment. Applying imaging cycler microscopy to analyse the immune contexture in a human skin cancer we could identify and map 7,000 distinct cell surface-associated multi-protein assemblies. The resulting combinatorial geometry-based high-functional resolution led to discovery of a mechanism of T cell trapping in the epidermis, which involves SPIKE, a network of suprabasal keratinocyte projections piercing and interconnecting CD8 T cells. It appears initiated by clusters of infrabasal T and dendritic cells connected via cell projections across a fractured basal lamina to suprabasal keratinocytes and T lymphocytes.

Specificity, polyspecificity, and heterospecificity of antibody-antigen recognition

The concept of antibody specificity is analyzed and shown to reside in the ability of an antibody to discriminate between two antigens. Initially, antibody specificity was attributed to sequence differences in complementarity determining regions (CDRs), but as increasing numbers of crystallographic antibody-antigen complexes were elucidated, specificity was analyzed in terms of six antigen-binding regions (ABRs) that only roughly correspond to CDRs. It was found that each ABR differs significantly in its amino acid composition and tends to bind different types of amino acids at the surface of proteins. In spite of these differences, the combined preference of the six ABRs does not allow epitopes to be distinguished from the rest of the protein surface. These findings explain the poor success of past and newly proposed methods for predicting protein epitopes. Antibody polyspecificity refers to the ability of one antibody to bind a large variety of epitopes in different antigens, and this property explains how the immune system develops an antibody repertoire that is able to recognize every antigen the system is likely to encounter. Antibody heterospecificity arises when an antibody reacts better with another antigen than with the one used to raise the antibody. As a result, an antibody may sometimes appear to have been elicited by an antigen with which it is unable to react. The implications of antibody polyspecificity and heterospecificity in vaccine development are pointed out.

Assessing the potential of atomistic molecular dynamics simulations to probe reversible protein-protein recognition and binding

Protein-protein recognition and binding are governed by diffusion, noncovalent forces and conformational flexibility, entangled in a way that only molecular dynamics simulations can dissect at high resolution. Here we exploited ubiquitin's noncovalent dimerization equilibrium to assess the potential of atomistic simulations to reproduce reversible protein-protein binding, by running submicrosecond simulations of systems with multiple copies of the protein at millimolar concentrations. The simulations essentially fail because they lead to aggregates, yet they reproduce some specificity in the binding interfaces as observed in known covalent and noncovalent ubiquitin dimers. Following similar observations in literature we hint at electrostatics and water descriptions as the main liable force field elements, and propose that their optimization should consider observables relevant to multi-protein systems and unfolded proteins. Within limitations, analysis of binding events suggests salient features of protein-protein recognition and binding, to be retested with improved force fields. Among them, that specific configurations of relative direction and orientation seem to trigger fast binding of two molecules, even over 50 Å distances; that conformational selection can take place within surface-to-surface distances of 10 to 40 Å i.e. well before actual intermolecular contact; and that establishment of contacts between molecules further locks their conformations and relative orientations.

Advances in toponomics drug discovery: Imaging cycler microscopy correctly predicts a therapy method of amyotrophic lateral sclerosis

An imaging cycler microscope (ICM) is a fully automated (epi)fluorescence microscope which overcomes the spectral resolution limit resulting in parameter- and dimension-unlimited fluorescence imaging. This enables the spatial resolution of large molecular systems with their emergent topological properties (toponome) in morphologically intact cells and tissues displaying thousands of multi protein assemblies at a time. The resulting combinatorial geometry of these systems has been shown to be key for in-vivo/in-situ detection of lead proteins controlling protein network topology and (dys)function: If lead proteins are blocked or downregulated the corresponding disease protein network disassembles. Here, correct therapeutic predictions are exemplified for ALS. ICM drug target studies have discovered an 18-dimensional cell surface molecular system in ALS-PBMC with a lead drug target protein, whose therapeutic downregulation is now reported to show statistically significant effect with stop of disease progression in one third of the ALS patients. Together, this clinical and the earlier experimental validations of the ICM approach indicate that ICM readily discovers in vivo robustness nodes of disease with lead proteins controlling them. Breaking in vivo robustness nodes using drugs against their lead proteins is likely to overcome current high drug attrition rates. © 2015 The Author. Published by Wiley Periodicals, Inc, on behalf of ISAC.