The mitophagy receptor Nix interacts with LC3/GABARAP proteins, targeting mitochondria into autophagosomes for degradation. Here we present evidence for phosphorylation-driven regulation of the Nix:LC3B interaction. Isothermal titration calorimetry and NMR indicate a ~100 fold enhanced affinity of the serine 34/35-phosphorylated Nix LC3-interacting region (LIR) to LC3B and formation of a very rigid complex compared to the non-phosphorylated sequence. Moreover, the crystal structure of LC3B in complex with the Nix LIR peptide containing glutamic acids as phosphomimetic residues and NMR experiments revealed that LIR phosphorylation stabilizes the Nix:LC3B complex via formation of two additional hydrogen bonds between phosphorylated serines of Nix LIR and Arg11, Lys49 and Lys51 in LC3B. Substitution of Lys51 to Ala in LC3B abrogates binding of a phosphomimetic Nix mutant. Functionally, serine 34/35 phosphorylation enhances autophagosome recruitment to mitochondria in HeLa cells. Together, this study provides cellular, biochemical and biophysical evidence that phosphorylation of the LIR domain of Nix enhances mitophagy receptor engagement.

Mitophagy is a conserved intracellular catabolic process responsible for the selective removal of dysfunctional or superfluous mitochondria to maintain mitochondrial quality and need in cells. Here, we examine the mechanisms of receptor-mediated mitophagy activation, with the focus on BNIP3L/NIX mitophagy receptor, proven to be indispensable for selective removal of mitochondria during the terminal differentiation of reticulocytes. The molecular mechanisms of selecting damaged mitochondria from healthy ones are still very obscure. We investigated BNIP3L dimerization as a potentially novel molecular mechanism underlying BNIP3L-dependent mitophagy. Forming stable homodimers, BNIP3L recruits autophagosomes more robustly than its monomeric form. Amino acid substitutions of key transmembrane residues of BNIP3L, BNIP3L^G204A or BNIP3L^G208V, led to the abolishment of dimer formation, resulting in the lower LC3A-BNIP3L recognition and subsequently lower mitophagy induction. Moreover, we identified the serine 212 as the main amino acid residue at the C-terminal of BNIP3L, which extends to the intermembrane space, responsible for dimerization. In accordance, the phosphomimetic mutation BNIP3L^S212E leads to a complete loss of BNIP3L dimerization. Thus, the interplay between BNIP3L phosphorylation and dimerization indicates that the combined mechanism of LIR phosphorylation and receptor dimerization is needed for proper BNIP3L-dependent mitophagy initiation and progression. Abbreviations: AMBRA1: autophagy and beclin 1 regulator 1; Baf A1: bafilomycin A₁; BH3: BCL2 homology 3; BNIP3: BCL2 interacting protein 3; BNIP3L/NIX: BCL2 interacting protein 3 like; CCCP: carbonyl cyanide 3-chlorophenylhydrazone; CoCl₂: cobalt (II) chloride; FKBP8: FKBP prolyl isomerase 8; FUNDC1: FUN14 domain containing 1; GABARAP: GABA type A receptor-associated protein; GST: glutathione S-transferase; IMM: inner mitochondrial membrane; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; OMM: outer mitochondrial membrane; PHB2: prohibitin 2; PI: propidium iodide; PINK1: PTEN induced kinase 1; TM: transmembrane domain; TOMM20: translocase of outer mitochondrial membrane 20

Adenine nucleotides (ANs)—adenosine 5′-triphosphate (ATP), adenosine 5′-diphosphate (ADP), and adenosine 5′-monophosphate (AMP)—are essential for energy transfer and the supply of countless processes within cellular metabolism. Their concentrations can be expressed as adenylate energy charge (AEC), a measure of cellular metabolic energy that directly correlates with the homeostasis of the organism. AEC index has broad diagnostic potential, as reduced ATP levels are associated to various conditions, such as inflammatory diseases, metabolic disorders, and cancer. We introduce a novel methodology for rapid isolation, purification, and quantification of ANs from a single drop of capillary blood. Of all the stationary phases tested, activated carbon proved to be the most efficient for the purification of adenine nucleotides, using an automated micro-solid phase extraction (µ-SPE) platform. An optimized µ-SPE method, coupled with RP-HPLC and a run time of 30 min, provides a reliable analytical framework for adenine nucleotide analysis of diverse biological samples. AN concentrations measured in capillary blood samples were 1393.1 µM, 254.8 µM, and 76.9 µM for ATP, ADP, and AMP molecules aligning with values reported in the literature. Overall, this study presents a streamlined and precise approach for analyzing ANs from microliters of blood, offering promising applications in clinical diagnostics.

Mitophagy, a selective clearance of damaged or superfluous mitochondria via autophagy machinery and lysosomal degradation, is an evolutionarily conserved process essential for various physiological functions, including cellular differentiation and immune responses. Defects in mitophagy are implicated in numerous human diseases, such as neurodegenerative disorders, cancer, and metabolic conditions. Despite significant advancements in mitophagy research over recent decades, novel and robust methodologies are necessary to elucidate its molecular mechanisms comprehensively. In this study, we present a detailed protocol for quantitatively assessing mitophagy through flow cytometry using a mitochondria‐targeted fluorescent mitophagy receptor, GFP‐BNIP3L/NIX. This method offers a rapid alternative to conventional microscopy or immunoblotting techniques for analyzing mitophagy activity. Additionally, this approach can theoretically be adapted to utilize any fluorescent‐tagged selective autophagy receptor, enabling the direct and rapid analysis of various types of receptor‐mediated selective autophagy.

We present a quantum-inspired model that embeds biomedical observables as state vectors in a Hilbert space, enabling the application of the full spectral theory of Hermitian operators and the identification of the system’s natural degrees of freedom as the eigenmodes of a constructed operator, for the analysis of high-dimensional, multifactorial, strongly correlated biomedical systems in which linear reductionist approaches are often insufficient to capture the underlying regulatory structure. Pairwise dependencies between variables are encoded in a Hermitian correlation operator whose off-diagonal elements are generalised mutual information quantities, estimated from joint and marginal Shannon entropies, providing consistent estimates for continuous variables without parametric assumptions. Diagonalisation of this operator yields eigenvalues that quantify the magnitudes of independent biomedical drivers and eigenvectors that identify the corresponding collective modes. Large eigenvalues correspond to dominant regulatory dimensions, while the full eigenvalue spectrum provides compact scalar measures of structural complexity, informational redundancy, and effective dimensionality. Unlike kernel PCA, which requires specification of a kernel function, and unlike linear PCA, which is restricted to second-order statistics, the proposed formalism captures nonlinear and non-Gaussian dependencies within a rigorous operator-algebraic framework whose eigenvalue spectrum is interpretable in terms of information content. We validate the model on a breast cancer gene expression benchmark spanning four molecular subtypes (three breast cancer subtypes and normal tissue), where it resolves five data-driven eigenmodes, two more than linear PCA, while three kernel PCA variants independently confirm the same subtype ordering as an intrinsic property of the data manifold, unifying linear, kernel, and information-theoretic correlation analysis within a single operator-algebraic framework. Collectively, these results indicate that the molecular organisation of the analysed benchmark is not driven by a small number of mutually independent variables but is instead distributed across several interconnected, nonlinear regulatory dimensions, underscoring the added biomedical interpretive value of the entropy-based operator relative to linear and kernel PCA.