Quantification and Comparison of Anti-Fibrotic Therapies by Polarized SRM and SHG-Based Morphometry in Rat UUO Model

Cyclin G1 induces maladaptive proximal tubule cell dedifferentiation and renal fibrosis through CDK5 activation

Acute kidney injury (AKI) occurs in approximately 13% of hospitalized patients and predisposes patients to chronic kidney disease (CKD) through the AKI-to-CKD transition. Studies from our laboratory and others have demonstrated that maladaptive repair of proximal tubule cells (PTCs), including induction of dedifferentiation, G2/M cell cycle arrest, senescence, and profibrotic cytokine secretion, is a key process promoting AKI-to-CKD transition, kidney fibrosis, and CKD progression. The molecular mechanisms governing maladaptive repair and the relative contribution of dedifferentiation, G2/M arrest, and senescence to CKD remain to be resolved. We identified cyclin G1 (CG1) as a factor upregulated in chronically injured and maladaptively repaired PTCs. We demonstrated that global deletion of CG1 inhibits G2/M arrest and fibrosis. Pharmacological induction of G2/M arrest in CG1-knockout mice, however, did not fully reverse the antifibrotic phenotype. Knockout of CG1 did not alter dedifferentiation and proliferation in the adaptive repair response following AKI. Instead, CG1 specifically promoted the prolonged dedifferentiation of kidney tubule epithelial cells observed in CKD. Mechanistically, CG1 promotes dedifferentiation through activation of cyclin-dependent kinase 5 (CDK5). Deletion of CDK5 in kidney tubule cells did not prevent G2/M arrest but did inhibit dedifferentiation and fibrosis. Thus, CG1 and CDK5 represent a unique pathway that regulates maladaptive, but not adaptive, dedifferentiation, suggesting they could be therapeutic targets for CKD.

Cyclo(Val-Pro) and Cyclo(Leu-Hydroxy-Pro) from Pseudomonas sp. (ABS-36) alleviates acute and chronic renal injury under in vitro and in vivo models (Ischemic reperfusion and unilateral ureter obstruction)

The study aimed to identify small molecules having potentiality in alleviating renal injury. Two natural compounds cyclo(Val-Pro) (1) and cyclo(Leu-Hydroxy-Pro) (2) were first evaluated under acute renal injury model of ischemic reperfusion at different doses of 25, 50 and 75 mg/kg body weight. Further, the compounds were subjected to antimycin A-induced ischemic in vitro study (NRK-52E cell lines). Both the compounds significantly decreased plasma IL-1β levels (P < 0.05). Also, the mRNA expression levels of inflammatory markers (TNF-α, IL-6 and IL-1β) and renal injury markers (KIM-1, NGAL, α-GST and π-GST) in the renal tissues were significantly alleviated (P < 0.01) along with the improvement in histological damage and control over neutrophil infiltration as a result of ischemic reperfusion. The in vitro study revealed the protective effect against antimycin A-induced cytotoxicity (P < 0.05) and antiapoptotic effect acting through the regulation of Bax, caspase 3 (pro and cleaved) and BCL2 with reduction in Annexin⁺PI⁺ cells. Further, the compound cyclo(Val-Pro) (1) was evaluated (50 mg/kg body weight dose) in chronic unilateral ureter obstruction model of renal injury in mice and TGF-β-induced in vitro fibrotic model (NRK-49F cell lines). Cyclo(Val-Pro) (1) significantly reduced the expression levels of fibrotic markers (collagen-1, α-SMA and TGF-β) and showed marked alleviation of renal fibrosis (sirius red staining). Also, the proliferation of TGF-β-induced NRK-49F cells was significantly reduced along with decreased levels of collagen-1 and α-SMA in immunohistochemistry studies. In conclusion, the compounds significantly abrogated ischemic injury by inhibiting renal inflammation and tubular epithelial apoptosis. Further, cyclo (Val-Pro) (1) exhibited significant anti-fibrotic activity through the inhibition of fibroblast activation and proliferation. Thus, these proline-based cyclic dipeptides are recommended as drug leads for treating renal injury.

Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples

Whole slide imaging, which is an important technique in the field of digital pathology, has recently been the subject of increased interest and avenues for utilisation, and with more widespread whole slide image (WSI) utilisation, there will also be increased interest in and implementation of image analysis (IA) techniques. IA includes artificial intelligence (AI) and targeted or hypothesis-driven algorithms. In the overall pathology field, the number of citations related to these topics has increased in recent years. Renal pathology is one anatomical pathology subspecialty that has utilised WSIs and IA algorithms; it can be argued that renal transplant pathology could be particularly suited for whole slide imaging and IA, as renal transplant pathology is frequently classified by use of the semiquantitative Banff classification of renal allograft pathology. Hypothesis-driven/targeted algorithms have been used in the past for the assessment of a variety of features in the kidney (e.g. interstitial fibrosis, tubular atrophy, inflammation); in recent years, the amount of research has particularly increased in the area of AI/machine learning for the identification of glomeruli, for histological segmentation, and for other applications. Deep learning is the form of machine learning that is most often used for such AI approaches to the 'big data' of pathology WSIs, and deep learning methods such as artificial neural networks (ANNs)/convolutional neural networks (CNNs) are utilised. Unsupervised and supervised AI algorithms can be employed to accomplish image or semantic classification. In this review, AI and other IA algorithms applied to WSIs are discussed, and examples from renal pathology are covered, with an emphasis on renal transplant pathology.

Advanced glycation end products cause RAGE-dependent annulus fibrosus collagen disruption and loss identified using in situ second harmonic generation imaging in mice intervertebral disk in vivo and in organ culture models

Aging and diabetes are associated with increased low-back pain and intervertebral disk (IVD) degeneration yet causal mechanisms remain uncertain. Advanced glycation end products (AGEs), which accumulate in IVDs from aging and are implicated in diabetes-related disorders, alter collagen and induce proinflammatory conditions. A need exists for methods that assess IVD collagen quality and degradation in order to better characterize specific structural changes in IVDs due to AGE accumulation and to identify roles for the receptor for AGEs (RAGE). We used multiphoton microscopy with second harmonic generation (SHG), collagen-hybridizing peptide (CHP), and image analysis methods to characterize effects of AGEs and RAGE on collagen quality and quantity in IVD annulus fibrosus (AF). First, we used SHG imaging on thin sections with an in vivo dietary mouse model and determined that high-AGE (H-AGE) diets increased AF fibril disruption and collagen degradation resulting in decreased total collagen content, suggesting an early degenerative cascade. Next, we used in situ SHG imaging with an ex vivo IVD organ culture model of AGE challenge on wild type and RAGE-knockout (RAGE-KO) mice and determined that early degenerative changes to collagen quality and degradation were RAGE dependent. We conclude that AGE accumulation leads to RAGE-dependent collagen disruption in the AF and can initiate molecular and tissue level collagen disruption. Furthermore, SHG and CHP analyzes were sensitive to collagenous alterations at multiple hierarchical levels due to AGE and may be useful in identifying additional contributors to collagen damage in IVD degeneration processes.

Banff Digital Pathology Working Group: Going digital in transplant pathology

The Banff Digital Pathology Working Group (DPWG) was formed in the time leading up to and during the joint American Society for Histocompatibility and Immunogenetics/Banff Meeting, September 23-27, 2019, held in Pittsburgh, Pennsylvania. At the meeting, the 14th Banff Conference, presentations directly and peripherally related to the topic of "digital pathology" were presented; and discussions before, during, and after the meeting have resulted in a list of issues to address for the DPWG. Included are practice standardization, integrative approaches for study classification, scoring of histologic parameters (eg, interstitial fibrosis and tubular atrophy and inflammation), algorithm classification, and precision diagnosis (eg, molecular pathways and therapeutics). Since the meeting, a survey with international participation of mostly pathologists (81%) was conducted, showing that whole slide imaging is available at the majority of centers (71%) but that artificial intelligence (AI)/machine learning was only used in ≈12% of centers, with a wide variety of programs/algorithms employed. Digitalization is not just an end in itself. It also is a necessary precondition for AI and other approaches. Discussions at the meeting and the survey highlight the unmet need for a Banff DPWG and point the way toward future contributions that can be made.

A practical new way to measure kidney fibrosis

Proper histological measurement of kidney fibrosis is essentially important in both clinical pathology and basic research using animal models of chronic kidney disease (CKD). However, standard histology techniques and their blind evaluation are cumbersome. Ranjit et al. applied an advanced optical microscopy technique for hassle-free, unbiased, and highly sensitive characterization of kidney fibrosis and tested it in a classic model of chronic kidney disease in mice. This commentary emphasizes the advantages and future promise of this new approach.

Cyclin G1 and TASCC regulate kidney epithelial cell G2-M arrest and fibrotic maladaptive repair

Fibrosis contributes to the progression of chronic kidney disease (CKD). Severe acute kidney injury can lead to CKD through proximal tubular cell (PTC) cycle arrest in the G₂-M phase, with secretion of profibrotic factors. Here, we show that epithelial cells in the G₂-M phase form target of rapamycin (TOR)-autophagy spatial coupling compartments (TASCCs), which promote profibrotic secretion similar to the senescence-associated secretory phenotype. Cyclin G1 (CG1), an atypical cyclin, promoted G₂-M arrest in PTCs and up-regulated TASCC formation. PTC TASCC formation was also present in humans with CKD. Prevention of TASCC formation in cultured PTCs blocked secretion of profibrotic factors. PTC-specific knockout of a key TASCC component reduced the rate of kidney fibrosis progression in mice with CKD. CG1 induction and TASCC formation also occur in liver fibrosis. Deletion of CG1 reduced G₂-M phase cells and TASCC formation in vivo. This study provides mechanistic evidence supporting how profibrotic G₂-M arrest is induced in kidney injury and how G₂-M-arrested PTCs promote fibrosis, identifying new therapeutic targets to mitigate kidney fibrosis.

Conditional deletion of RB1 in the Tie2 lineage leads to aortic valve regurgitation

Objective

Aortic valve disease is a complex process characterized by valve interstitial cell activation, disruption of the extracellular matrix culminating in valve mineralization occurring over many years. We explored the function of the retinoblastoma protein (pRb) in aortic valve disease, given its critical role in mesenchymal cell differentiation including bone development and mineralization.

Approach and results

We generated a mouse model of conditional pRb knockout (cKO) in the aortic valve regulated by Tie2-Cre-mediated excision of floxed RB1 alleles. Aged pRb cKO animals showed significantly more aortic valve regurgitation by echocardiography compared to pRb het control animals. The pRb cKO aortic valves had increased leaflet thickness without increased cellular proliferation. Histologic studies demonstrated intense α-SMA expression in pRb cKO leaflets associated with disorganized extracellular matrix and increased leaflet stiffness. The pRb cKO mice also showed increased circulating cytokine levels.

Conclusions

Our studies demonstrate that pRb loss in the Tie2-lineage that includes aortic valve interstitial cells is sufficient to cause age-dependent aortic valve dysfunction.

Determination of extracellular matrix collagen fibril architectures and pathological remodeling by polarization dependent second harmonic microscopy

Polarization dependence second harmonic generation (P-SHG) microscopy is gaining increase popularity for in situ quantification of fibrillar protein architectures. In this report, we combine P-SHG microscopy, new linear least square (LLS) fitting and modeling to determine and convert the complex second-order non-linear optical anisotropy parameter ρ of several collagen rich tissues into a simple geometric organization of collagen fibrils. Modeling integrates a priori knowledge of polyhelical organization of collagen molecule polymers forming fibrils and bundles of fibrils as well as Poisson photonic shot noise of the detection system. The results, which accurately predict the known sub-microscopic hierarchical organization of collagen fibrils in several tissues, suggest that they can be subdivided into three classes according to their microscopic and macroscopic hierarchical organization of collagen fibrils. They also show, for the first time to our knowledge, intrahepatic spatial discrimination between genuine fibrotic and non-fibrotic vessels. CCl₄-treated livers are characterized by an increase in the percentage of fibrotic vessels and their remodeling involves peri-portal compaction and alignment of collagen fibrils that should contribute to portal hypertension. This integrated P-SHG image analysis method is a powerful tool that should open new avenue for the determination of pathophysiological and chemo-mechanical cues impacting collagen fibrils organization.