Label-free macrophage phenotype classification using machine learning methods

Effects of bone surface topography and chemistry on macrophage polarization

Surface structure plays a crucial role in determining cell behavior on biomaterials, influencing cell adhesion, proliferation, differentiation, as well as immune cells and macrophage polarization. While grooves and ridges stimulate M2 polarization and pits and bumps promote M1 polarization, these structures do not accurately mimic the real bone surface. Consequently, the impact of mimicking bone surface topography on macrophage polarization remains unknown. Understanding the synergistic sequential roles of M1 and M2 macrophages in osteoimmunomodulation is crucial for effective bone tissue engineering. Thus, exploring the impact of bone surface microstructure mimicking biomaterials on macrophage polarization is critical. In this study, we aimed to sequentially activate M1 and M2 macrophages using Poly-L-Lactic acid (PLA) membranes with bone surface topographical features mimicked through the soft lithography technique. To mimic the bone surface topography, a bovine femur was used as a model surface, and the membranes were further modified with collagen type-I and hydroxyapatite to mimic the bone surface microenvironment. To determine the effect of these biomaterials on macrophage polarization, we conducted experimental analysis that contained estimating cytokine release profiles and characterizing cell morphology. Our results demonstrated the potential of the hydroxyapatite-deposited bone surface-mimicked PLA membranes to trigger sequential and synergistic M1 and M2 macrophage polarizations, suggesting their ability to achieve osteoimmunomodulatory macrophage polarization for bone tissue engineering applications. Although further experimental studies are required to completely investigate the osteoimmunomodulatory effects of these biomaterials, our results provide valuable insights into the potential advantages of biomaterials that mimic the complex microenvironment of bone surfaces.

Metabolic regulation of tumor-associated macrophage heterogeneity: insights into the tumor microenvironment and immunotherapeutic opportunities

Tumor-associated macrophages (TAMs) are a heterogeneous population that play diverse functions in tumors. Their identity is determined not only by intrinsic factors, such as origins and transcription factors, but also by external signals from the tumor microenvironment (TME), such as inflammatory signals and metabolic reprogramming. Metabolic reprogramming has rendered TAM to exhibit a spectrum of activities ranging from pro-tumorigenic to anti-tumorigenic, closely associated with tumor progression and clinical prognosis. This review implicates the diversity of TAM phenotypes and functions, how this heterogeneity has been re-evaluated with the advent of single-cell technologies, and the impact of TME metabolic reprogramming on TAMs. We also review current therapies targeting TAM metabolism and offer new insights for TAM-dependent anti-tumor immunotherapy by focusing on the critical role of different metabolic programs in TAMs.

Prediction of six macrophage phenotypes and their IL-10 content based on single-cell morphology using artificial intelligence

Introduction

The last decade has led to rapid developments and increased usage of computational tools at the single-cell level. However, our knowledge remains limited in how extracellular cues alter quantitative macrophage morphology and how such morphological changes can be used to predict macrophage phenotype as well as cytokine content at the single-cell level.

Methods

Using an artificial intelligence (AI) based approach, this study determined whether (i) accurate macrophage classification and (ii) prediction of intracellular IL-10 at the single-cell level was possible, using only morphological features as predictors for AI. Using a quantitative panel of shape descriptors, our study assessed image-based original and synthetic single-cell data in two different datasets in which CD14+ monocyte-derived macrophages generated from human peripheral blood monocytes were initially primed with GM-CSF or M-CSF followed by polarization with specific stimuli in the presence/absence of continuous GM-CSF or M-CSF. Specifically, M0, M1 (GM-CSF-M1, TNFα/IFNγ-M1, GM-CSF/TNFα/IFNγ-M1) and M2 (M-CSF-M2, IL-4-M2a, M-CSF/IL-4-M2a, IL-10-M2c, M-CSF/IL-10-M2c) macrophages were examined.

Results

Phenotypes were confirmed by ELISA and immunostaining of CD markers. Variations of polarization techniques significantly changed multiple macrophage morphological features, demonstrating that macrophage morphology is a highly sensitive, dynamic marker of phenotype. Using original and synthetic single-cell data, cell morphology alone yielded an accuracy of 93% for the classification of 6 different human macrophage phenotypes (with continuous GM-CSF or M-CSF). A similarly high phenotype classification accuracy of 95% was reached with data generated with different stimuli (discontinuous GM-CSF or M-CSF) and measured at a different time point. These comparably high accuracies clearly validated the here chosen AI-based approach. Quantitative morphology also allowed prediction of intracellular IL-10 with 95% accuracy using only original data.

Discussion

Thus, image-based machine learning using morphology-based features not only (i) classified M0, M1 and M2 macrophages but also (ii) classified M2a and M2c subtypes and (iii) predicted intracellular IL-10 at the single-cell level among six phenotypes. This simple approach can be used as a general strategy not only for macrophage phenotyping but also for prediction of IL-10 content of any IL-10 producing cell, which can help improve our understanding of cytokine biology at the single-cell level.

Two new clades recovered at high temperatures provide novel phylogenetic and genomic insights into Candidatus Accumulibacter

Candidatus Accumulibacter, a key genus of polyphosphate-accumulating organisms, plays key roles in lab- and full-scale enhanced biological phosphorus removal (EBPR) systems. A total of 10 high-quality Ca. Accumulibacter genomes were recovered from EBPR systems operated at high temperatures, providing significantly updated phylogenetic and genomic insights into the Ca. Accumulibacter lineage. Among these genomes, clade IIF members SCELSE-3, SCELSE-4, and SCELSE-6 represent the to-date known genomes encoding a complete denitrification pathway, suggesting that Ca. Accumulibacter alone could achieve complete denitrification. Clade IIC members SSA1, SCUT-1, SCELCE-2, and SCELSE-8 lack the entire set of denitrifying genes, representing to-date known non-denitrifying Ca. Accumulibacter. A pan-genomic analysis with other Ca. Accumulibacter members suggested that all Ca. Accumulibacter likely has the potential to use dicarboxylic amino acids. Ca. Accumulibacter aalborgensis AALB and Ca. Accumulibacter affinis BAT3C720 seemed to be the only two members capable of using glucose for EBPR. A heat shock protein Hsp20 encoding gene was found exclusively in genomes recovered at high temperatures, which was absent in clades IA, IC, IG, IIA, IIB, IID, IIG, and II-I members. High transcription of this gene in clade IIC members SCUT-2 and SCUT-3 suggested its role in surviving high temperatures for Ca. Accumulibacter. Ambiguous clade identity was observed for newly recovered genomes (SCELSE-9 and SCELSE-10). Five machine learning models were developed using orthogroups as input features. Prediction results suggested that they belong to a new clade (IIK). The phylogeny of Ca. Accumulibacter was re-evaluated based on the laterally derived polyphosphokinase 2 gene, showing improved resolution in differentiating different clades.

Unraveling the potential of 3D bioprinted immunomodulatory materials for regulating macrophage polarization: State-of-the-art in bone and associated tissue regeneration

Macrophage-assisted immunomodulation is an alternative strategy in tissue engineering, wherein the interplay between pro-inflammatory and anti-inflammatory macrophage cells and body cells determines the fate of healing or inflammation. Although several reports have demonstrated that tissue regeneration depends on spatial and temporal regulation of the biophysical or biochemical microenvironment of the biomaterial, the underlying molecular mechanism behind immunomodulation is still under consideration for developing immunomodulatory scaffolds. Currently, most fabricated immunomodulatory platforms reported in the literature show regenerative capabilities of a particular tissue, for example, endogenous tissue (e.g., bone, muscle, heart, kidney, and lungs) or exogenous tissue (e.g., skin and eye). In this review, we briefly introduced the necessity of the 3D immunomodulatory scaffolds and nanomaterials, focusing on material properties and their interaction with macrophages for general readers. This review also provides a comprehensive summary of macrophage origin and taxonomy, their diverse functions, and various signal transduction pathways during biomaterial-macrophage interaction, which is particularly helpful for material scientists and clinicians for developing next-generation immunomodulatory scaffolds. From a clinical standpoint, we briefly discussed the role of 3D biomaterial scaffolds and/or nanomaterial composites for macrophage-assisted tissue engineering with a special focus on bone and associated tissues. Finally, a summary with expert opinion is presented to address the challenges and future necessity of 3D bioprinted immunomodulatory materials for tissue engineering.