Leishmania amazonensis promastigotes in 3D Collagen I culture: an in vitro physiological environment for the study of extracellular matrix and host cell interactions

Leishmania amazonensis is the causative agent of American cutaneous leishmaniasis, an important neglected tropical disease. Once Leishmania amazonensis is inoculated into the human host, promastigotes are exposed to the extracellular matrix (ECM) of the dermis. However, little is known about the interaction between the ECM and Leishmania promastigotes. In this study we established L. amazonensis promastigote culture in a three-dimensional (3D) environment mainly composed of Collagen I (COL I). This 3D culture recreates in vitro some aspects of the human host infection site, enabling the study of the interaction mechanisms of L. amazonensis with the host ECM. Promastigotes exhibited “freeze and run” migration in the 3D COL I matrix, which is completely different from the conventional in vitro swimming mode of migration. Moreover, L. amazonensis promastigotes were able to invade, migrate inside, and remodel the 3D COL I matrix. Promastigote trans-matrix invasion and the freeze and run migration mode were also observed when macrophages were present in the matrix. At least two classes of proteases, metallo- and cysteine proteases, are involved in the 3D COL I matrix degradation caused by Leishmania. Treatment with a mixture of protease inhibitors significantly reduced promastigote invasion and migration through this matrix. Together our results demonstrate that L. amazonensis promastigotes release proteases and actively remodel their 3D environment, facilitating their migration. This raises the possibility that promastigotes actively interact with their 3D environment during the search for their cellular “home”—macrophages. Supporting this hypothesis, promastigotes migrated faster than macrophages in a novel 3D co-culture model

Introducing an automated high content confocal imaging approach for Organs-on-Chips

Organ-Chips are micro-engineered systems that aim to recapitulate the organ microenvironment. Implementation of Organ-Chips within the pharmaceutical industry aims to improve the probability of success of drugs reaching late stage clinical trial by generating models for drug discovery that are of human origin and have disease relevance. We are adopting the use of Organ-Chips for enhancing pre-clinical efficacy and toxicity evaluation and prediction. Whilst capturing cellular phenotype via imaging in response to drug exposure is a useful readout in these models, application has been limited due to difficulties in imaging the chips at scale. Here we created an end-to-end, automated workflow to capture and analyse confocal images of multicellular Organ-Chips to assess detailed cellular phenotype across large batches of chips. By automating this process, we not only reduced acquisition time, but we also minimised process variability and user bias. This enabled us to establish, for the first time, a framework of statistical best practice for Organ-Chip imaging, creating the capability of using Organ-Chips and imaging for routine testing in drug discovery applications that rely on quantitative image data for decision making. We tested our approach using benzbromarone, whose mechanism of toxicity has been linked to mitochondrial damage with subsequent induction of apoptosis and necrosis, and staurosporine, a tool inducer of apoptosis. We also applied this workflow to assess the hepatotoxic effect of an active AstraZeneca drug candidate illustrating its applicability in drug safety assessment beyond testing tool compounds. Finally, we have demonstrated that this approach could be adapted to Organ-Chips of different shapes and sizes through application to a Kidney-Chip.</p

A New Human 3D-Liver Model Unravels the Role of Galectins in Liver Infection by the Parasite <i>Entamoeba histolytica</i>

<div><p>Investigations of human parasitic diseases depend on the availability of appropriate <i>in vivo</i> animal models and <i>ex vivo</i> experimental systems, and are particularly difficult for pathogens whose exclusive natural hosts are humans, such as <i>Entamoeba histolytica</i>, the protozoan parasite responsible for amoebiasis. This common infectious human disease affects the intestine and liver. In the liver sinusoids <i>E. histolytica</i> crosses the endothelium and penetrates into the parenchyma, with the concomitant initiation of inflammatory foci and subsequent abscess formation. Studying factors responsible for human liver infection is hampered by the complexity of the hepatic environment and by the restrictions inherent to the use of human samples. Therefore, we built a human 3D-liver <i>in vitro</i> model composed of cultured liver sinusoidal endothelial cells and hepatocytes in a 3D collagen-I matrix sandwich. We determined the presence of important hepatic markers and demonstrated that the cell layers function as a biological barrier. <i>E. histolytica</i> invasion was assessed using wild-type strains and amoebae with altered virulence or different adhesive properties. We showed for the first time the dependence of endothelium crossing upon amoebic Gal/GalNAc lectin. The 3D-liver model enabled the molecular analysis of human cell responses, suggesting for the first time a crucial role of human galectins in parasite adhesion to the endothelial cells, which was confirmed by siRNA knockdown of galectin-1. Levels of several pro-inflammatory cytokines, including galectin-1 and -3, were highly increased upon contact of <i>E. histolytica</i> with the 3D-liver model. The presence of galectin-1 and -3 in the extracellular medium stimulated pro-inflammatory cytokine release, suggesting a further role for human galectins in the onset of the hepatic inflammatory response. These new findings are relevant for a better understanding of human liver infection by <i>E. histolytica</i>.</p></div

Human released or cell surface-associated proteins identified in the medium on top of the 3D-liver model during <i>E. histolytica</i> invasion (specific for the 3D-liver model with amoebae).

<p>Proteome data after BLAST search with the <i>H. sapiens</i> UniProt database (samples from 9 biological replicates) and two-stage filtering (i.e. elimination of bovine matches and subtraction of proteins identified in the model without amoebae) identified 139 proteins having at least one human-specific peptide (see <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004381#ppat.1004381.s005" target="_blank">Table S1</a> and <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004381#ppat.1004381.s006" target="_blank">S2</a>). Further analysis was performed to identify secreted and cell membrane-associated proteins performing a literature search and information contained in the UniProtKB/Swiss-Prot database. For the 24 proteins found, their main function (given by the UniProtKB/Swiss-Prot database) is indicated in the table. Database accession numbers are provided. The proteins were ranked according to the number of samples in which they were found (decreasing from top to bottom). Bold-labelled entries correspond to those proteins for which hepatic cells are known to be the exclusive or a main site of synthesis. The numbers given are average from all samples. PSMS is peptide spectrum matches, MW molecular weight.</p><p>Human released or cell surface-associated proteins identified in the medium on top of the 3D-liver model during <i>E. histolytica</i> invasion (specific for the 3D-liver model with amoebae).</p

Kinetics of cytokine release in the 3D-liver model in response to <i>E. histolytica</i>.

<p>Quantification in fractions S1 (A–C, E–F) or S3 (D) after addition to the 3D-liver models of fresh serum-free medium containing virulent <i>E. histolytica</i>. Graphs with standard deviation and statistical evaluation by One way ANOVA, p<0.001**, <0.0001*** for minimal 3 independent experiments. CTL is incubation for 6 h without amoebae. n/d = not detected.</p

<i>E. histolytica</i> binding to human galectin-1 and -3.

<p>Bacterially expressed purified human galectin-1 and -3, and BSA as a control, were used for the incubations with the amoebae. Galectin-1 (A) or -3 (B) binding to the trophozoite surface, visualized by immunofluorescence with human galectin-specific antibodies. Quantification of galectin-1 (C) or -3 (D) binding to immobilized trophozoites by ELISA-like assays. (E) Trophozoite adhesion to immobilized galectin-1 or -3 and competition with lactose (lac).</p

Human cytokine and growth factor profile in the absence or the presence of <i>E. histolytica</i>.

<p>(A–D) ELISA quantification in compartments S1, S2 and S3 of the 3D-liver model (Model) or the setup without LSEC (no LSEC), in the absence or the presence of <i>E. histolytica</i> (− or + Eh). Samples used for ELISA assays were prepared as for <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004381#ppat-1004381-g004" target="_blank">Figure 4</a>. (A) Amounts of IL-6 at 3 h, (B) IL-1β, (C) galectin-1 and (D) galectin-3 at 6 h of incubation with fresh serum-free medium containing or not virulent <i>E. histolytica</i>. Graphs with standard deviation and statistical evaluation by One way ANOVA, p<0.01*, <0.001**, <0.0001*** for 3–5 independent experiments. None of the cytokines was detected in the COL-I matrix control without hepatic cells. n/d = not detected. (E, F) Summary of the results from <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004381#ppat-1004381-g004" target="_blank">Figure 4</a> and <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004381#ppat-1004381-g005" target="_blank">Figure 5</a>, for the setup without LSEC (E) and the 3D-liver model (F), showing the complexity of the pro-inflammatory response induced by <i>E. histolytica</i> in the 3D-liver model.</p

<i>E. histolytica</i> crossing and invasion.

<p>(A) Transversal view of 3D reconstructed two-photon microscopy and SHG images (ICY software) of the 3D-liver model or the setup without LSEC (No LSEC) after 3 h of interaction with virulent amoebae. Hepatic cells (red), amoebae (green) and COL-I (blue). (B–E) Quantification of the amoebae crossing the 3D-liver model or the different setups, expressed as the percentage of amoebae crossing the LSEC layer or penetrating the COL-I matrix, from the total number of amoebae in the field. (B) Incubation of the 3D-liver model with virulent amoebae for 1.5 h and 3 h. (C) Incubation of the different setups with virulent amoebae for 3 h. (D–E) Incubations with different amoebae strains, and with glucose or galactose of (D) the 3D-liver model for 1.5 h, or (E) the setup without LSEC for 3 h. Values obtained for incubations with virulent trophozoites in the absence or the presence of glucose, or with the HGL-2 control trophozoites transfected with the vector not containing Gal/GalNAc lectin sequences, were not significantly different and are thus represented together as control (CTL). (F) Amoebic invasion rate at 3 h, in the presence (Model) or in the absence (No LSEC) of LSEC, with 0% invasion set at the LSEC and 100% at the hepatocyte layer z-position. Red bars indicate the means. Graphs with standard deviations and statistical evaluation by One way ANOVA, p<0.01*, <0.0001*** for n = 50 of minimal 3 independent experiments. (G–I) Amoebic interactions (3 h) with the LSEC layer of the 3D-liver model. (G–H) Arrows point to LSEC detaching in the vicinity of amoebae (I). Asterisks mark vesicular structures localized inside trophozoites and labelled with cell tracker used for hepatic cell staining.</p

Expression of hepatocyte functions in the human 3D-liver model.

<p>(A) Schematic representation of the different set-ups used for the analyses. Standard 2D Huh-7 monocultures (2D hepatocytes), the COL-I sandwich with a Huh-7 monolayer (no LSEC) and the 3D-liver model with a Huh-7 and LSEC layer. (B) Human albumin secretion into the medium on top of the cultures measured by ELISA. Cultures were used 3d after seeding. Albumin secretion into fresh serum-free medium was determined after 1.5–6 h incubation. (C, D) Expression of hepatocyte markers by Q-RT-PCR analysis (see <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004381#ppat.1004381.s003" target="_blank">Figure S3</a> for complete datasets). (C) Amount of transcripts expressed in the 3D-liver model monitored over time of culture (3–14d). Changes in transcript levels were expressed as log2-fold changes in comparison to levels determined for the 3d cultures (set to 0). The graph represents the 5 markers whose expression was maintained over time. (D) Transcript levels in 3d cultures represented as log2-fold changes over levels in 2D Huh-7 cultures (set to 0). The graph shows the functions for which the levels were significantly increased. Note that for the 3D-liver model, normalization of Q-PCR data with GAPDH (expressed by both hepatocytes and LSEC) leads to an underestimation of the transcript level for the hepatocyte-specific markers.</p

Galectin-1 and -3 dependent adhesion of <i>E. histolytica</i> to human hepatic cells.

<p>Immunofluorescence localization of cell surface-associated (A) galectin-3 on Huh-7 and (C) galectin-1 on LSEC. Amoeba adhesion to (B) Huh-7 or (D) LSEC 2D cultures Control (CTL), corresponding to incubations without proteins or sugars added, was set to 100%. (E) LSEC galectin-1 surface label 72 h after transfection with galectin-1 specific siRNA. (F) Amoeba binding to LSEC transfected with galectin-1 specific or unrelated control siRNA. Incubations and quantification of trophozoite binding as for B and D. Graphs with standard deviation and statistical evaluation by One way ANOVA, p<0.0001*** for 3 independent experiments.</p