Behavioral immune landscapes of inflammation.

Transcriptional or proteomic profiling of individual cells have revolutionized interpretation of biological phenomena by providing cellular landscapes of healthy and diseased tissues. These approaches, however, fail to describe dynamic scenarios in which cells can change their biochemical properties and downstream “behavioral” outputs every few seconds or minutes. Here, we used 4D live imaging to record tens to hundreds of morpho-kinetic parameters describing the dynamism of individual leukocytes at sites of active inflammation. By analyzing over 100,000 reconstructions of cell shapes and tracks over time, we obtained behavioral descriptors of individual cells and used these high-dimensional datasets to build behavioral landscapes. These landscapes recognized leukocyte identities in the inflamed skin and trachea, and inside blood vessels uncovered a continuum of neutrophil states, including a large, sessile state that was embraced by the underlying endothelium and associated with pathogenic inflammation. Behavioral in vivo screening of thousands of cells from 24 different mouse mutants identified the kinase Fgr as a driver of this pathogenic state, and genetic or pharmacological interference of Fgr protected from inflammatory injury. Thus, behavioral landscapes report unique biological properties of dynamic environments at high cellular, spatial and temporal resolution.pre-print4302 K

Variable selection for nonlinear dimensionality reduction of biological datasets through bootstrapping of correlation networks.

Identifying the most relevant variables or features in massive datasets for dimensionality reduction can lead to improved and more informative display, faster computation times, and more explainable models of complex systems. Despite significant advances and available algorithms, this task generally remains challenging, especially in unsupervised settings. In this work, we propose a method that constructs correlation networks using all intervening variables and then selects the most informative ones based on network bootstrapping. The method can be applied in both supervised and unsupervised scenarios. We demonstrate its functionality by applying Uniform Manifold Approximation and Projection for dimensionality reduction to several high-dimensional biological datasets, derived from 4D live imaging recordings of hundreds of morpho-kinetic variables, describing the dynamics of thousands of individual leukocytes at sites of prominent inflammation. We compare our method with other standard ones in the field, such as Principal Component Analysis and Elastic Net, showing that it outperforms them. The proposed method can be employed in a wide range of applications, encompassing data analysis and machine learning.This research has been supported by grants awarded to G.F.C. by the Spanish Ministerio de Ciencia e Innovación and the European Union NextGenerationEU/PRTR, MCIN/AEI/10.13039/501100011033 (grant numbers TED2021-132296B-C55, PDC2022-133520-I00 and PID2022- 142341OB-I00). D.G.A., Spain is supported by a research contract with reference 2023-CDT-11616 (from project with grant number TED2021- 132296B-C55). A.H. was supported by RTI2018-095497-B-I00 from Ministerio de Ciencia e Innovación (MCIN), Spain, HR17_00527 from Fundación La Caixa, Spain, Transatlantic Network of Excellence, Spain (TNE-18CVD04) from the Leducq Foundation, and FET-OPEN (no. 861878) from the European Comission. M.P.-S. is supported by a Federation of European Biochemical Societies, Spain, the EMBO ALTF (no. 1142–2020) long-term fellowship and from MICINN, Spain (RYC2021- 033511-I). J.S. is supported by a fellowship (PRE2019-089130) from MICINN, Spain. The CNIC is supported by the MCIN and the Pro-CNIC Foundation, Spain.S

BMAL1-Driven Tissue Clocks Respond Independently to Light to Maintain Homeostasis

Circadian rhythms control organismal physiology throughout the day. At the cellular level, clock regulation is established by a self-sustained Bmal1-dependent transcriptional oscillator network. However, it is still unclear how different tissues achieve a synchronized rhythmic physiology. That is, do they respond independently to environmental signals, or require interactions with each other to do so? We show that unexpectedly, light synchronizes the Bmal1-dependent circadian machinery in single tissues in the absence of Bmal1 in all other tissues. Strikingly, light-driven tissue autonomous clocks occur without rhythmic feeding behavior and are lost in constant darkness. Importantly, tissue-autonomous Bmal1 partially sustains homeostasis in otherwise arrhythmic and prematurely aging animals. Our results therefore support a two-branched model for the daily synchronization of tissues: an autonomous response branch, whereby light entrains circadian clocks without any commitment of other Bmal1-dependent clocks, and a memory branch using other Bmal1-dependent clocks to “remember” time in the absence of external cues

BMAL1-Driven Tissue Clocks Respond Independently to Light to Maintain Homeostasis

Circadian rhythms control organismal physiology throughout the day. At the cellular level, clock regulation is established by a self-sustained Bmal1-dependent transcriptional oscillator network. However, it is still unclear how different tissues achieve a synchronized rhythmic physiology. That is, do they respond independently to environmental signals, or require interactions with each other to do so? We show that unexpectedly, light synchronizes the Bmal1-dependent circadian machinery in single tissues in the absence of Bmal1 in all other tissues. Strikingly, light-driven tissue autonomous clocks occur without rhythmic feeding behavior and are lost in constant darkness. Importantly, tissue-autonomous Bmal1 partially sustains homeostasis in otherwise arrhythmic and prematurely aging animals. Our results therefore support a two-branched model for the daily synchronization of tissues: an autonomous response branch, whereby light entrains circadian clocks without any commitment of other Bmal1-dependent clocks, and a memory branch using other Bmal1-dependent clocks to “remember” time in the absence of external cues

Neutrophils instruct homeostatic and pathological states in naïve tissues

Immune protection relies on the capacity of neutrophils to infiltrate challenged tissues. Naive tissues, in contrast, are believed to remain free of these cells and protected from their toxic cargo. Here, we show that neutrophils are endowed with the capacity to infiltrate multiple tissues in the steady-state, a process that follows tissue-specific dynamics. By focusing in two particular tissues, the intestine and the lungs, we find that neutrophils infiltrating the intestine are engulfed by resident macrophages, resulting in repression of Il23 transcription, reduced G-CSF in plasma, and reinforced activity of distant bone marrow niches. In contrast, diurnal accumulation of neutrophils within the pulmonary vasculature influenced circadian transcription in the lungs. Neutrophil-influenced transcripts in this organ were associated with carcinogenesis and migration. Consistently, we found that neutrophils dictated the diurnal patterns of lung invasion by melanoma cells. Homeostatic infiltration of tissues unveils a facet of neutrophil biology that supports organ function, but can also instigate pathological states

A network of macrophages supports mitochondrial homeostasis in the heart

Cardiomyocytes are subjected to the intense mechanical stress and metabolic demands of the beating heart. It is unclear whether these cells, which are long-lived and rarely renew, manage to preserve homeostasis on their own. While analyzing macrophages lodged within the healthy myocardium, we discovered that they actively took up material, including mitochondria, derived from cardiomyocytes. Cardiomyocytes ejected dysfunctional mitochondria and other cargo in dedicated membranous particles reminiscent of neural exophers, through a process driven by the cardiomyocyte’s autophagy machinery that was enhanced during cardiac stress. Depletion of cardiac macrophages or deficiency in the phagocytic receptor Mertk resulted in defective elimination of mitochondria from the myocardial tissue, activation of the inflammasome, impaired autophagy, accumulation of anomalous mitochondria in cardiomyocytes, metabolic alterations, and ventricular dysfunction. Thus, we identify an immune-parenchymal pair in the murine heart that enables transfer of unfit material to preserve metabolic stability and organ function

A Network of Macrophages Supports Mitochondrial Homeostasis in the Heart

Cardiomyocytes are subjected to the intense mechanical stress and metabolic demands of the beating heart. It is unclear whether these cells, which are long-lived and rarely renew, manage to preserve homeostasis on their own. While analyzing macrophages lodged within the healthy myocardium, we discovered that they actively took up material, including mitochondria, derived from cardiomyocytes. Cardiomyocytes ejected dysfunctional mitochondria and other cargo in dedicated membranous particles reminiscent of neural exophers, through a process driven by the cardiomyocyte's autophagy machinery that was enhanced during cardiac stress. Depletion of cardiac macrophages or deficiency in the phagocytic receptor Mertk resulted in defective elimination of mitochondria from the myocardial tissue, activation of the inflammasome, impaired autophagy, accumulation of anomalous mitochondria in cardiomyocytes, metabolic alterations, and ventricular dysfunction. Thus, we identify an immune-parenchymal pair in the murine heart that enables transfer of unfit material to preserve metabolic stability and organ function. Video Abstract: [Figure presented] A system of macrophages in the heart supports cardiomyocyte health by phagocytosing exopher particles ejected from cardiomyocytes that contain defective mitochondria, among other cellular contents.This study was supported by Intramural grants from the Severo Ochoa program (IGP-SO); grants SAF2015-71878-REDT and SAF2014-56819-R from the Ministerio de Ciencia e Innovacion (MICINN) to A.C.; European Research Council grant EU-rhythmy (ERC-ADG-2014-ID:669387) to S.G.P., and MATRIX (ERC-COG-2018-ID: 819775) to B.I.; L.G.N. is supported by SIgN core funding from A∗STAR; grant BFU2016-75144-R from the Ministry of Science and Innovation to J.A.B,; grants PGC2018-096486-B-I00 and RD16/0011/0019 (ISCIII) from MICINN, TNE-17CVD04 from the Leducq Foundation, and S2017/BMD-3875 from the Comunidad de Madrid to M.T; intramural grant TPC/O-SO and grants SAF2015-65633-R, RTI2018-099357-B-I00, and HFSP (RGP0016/2018) to J.A.E.; intramural grant IGP-SO to J.A.-C. and A.H.; BIO2017-83640-P and RYC-2014-16604 to J.A-C; grants PRB3 (IPT17/0019-ISCIII-SGEFI/ERDF, ProteoRed) from the Carlos III Institute of Health and Fondo de Investigaciones Sanitarias, BIO2015-67580-P and PGC2018-097019-B-I00 from MICINN to J.V.; RTI2018-096068 from MICINN, AFM, MDA, LaCaixa-HR17-00040, UPGRADE-H2020-825825, and European Research Council (ERC-741538) to P.M.C.; S2017/BMD-3867 RENIM-CM from the Comunidad de Madrid and cofunded with European structural and investment funds to M.D.; 120/C/2015-20153032 from Fundació la Marató de TV3, SAF2015-65607-R and RTI2018-095497-B-I00 from MICINN, HR17_00527 from La Caixa Foundation, and TNE-18CVD04 from the Leducq Foundation to A.H.; C.V.R. is a Howard Hughes Medical Institute Faculty Scholar; J.A.N-A is supported by fellowship SVP-2014-068595, A.V.L.-V. by SVP-2013-068089, L.E.-M. by FJCI-2016-29384, and A.R.-P. by BES-2016-076635, all from MICINN; and the CNIC International Postdoctoral Program (EU grant agreement 600396 to D.J.S.). The CNIC is supported by the MICINN and the Pro-CNIC Foundation and is a Severo Ochoa Center of Excellence (MICINN award SEV-2015-0505)